Schematics for replacement of the unknown Sxl-GFP nuclear background with the isogenic w1118 background
Figure S1: Crossing scheme used to create a standard homozygous GFP-w line. Males from this line were crossed with females carrying a specific mitochondrial haplotype, to create experimental mitolines. These newly produced lines carried the mitochondrial haplotype of the female and were heterozygous for the Sxl-GFP construct. G1 = the first generation of the cross.
Here we include all code used to run our analysis, our rationale behind the modelling approaches, and all remaining supplementary tables and figures.
# load relevant packages
library(lme4) # for the lmer and glmer mixed model functions
library(lmerTest) # Used to get p-values for lmer models using simulation. It over-writes lmer() with a new version, which gives p-values
library(glmmTMB) # for zero-inflated or hurdle glms
library(brms) # for Bayesian models
library(car) # for type III Anova's
library(dplyr) # data re-shaping
library(MuMIn) # for model selection and averaging
library(ggplot2) # for plots
library(ggThemeAssist) # a plot formatting add in
library(ggridges) # for joy plots
library(ggExtra) # for ggplot enhancements - primarily ggMarginal()
library(ggstance) # for ggplot enhancements - can create more horizontal plots
library(ggpubr) # for the ggarrange function
library(ggbeeswarm) # violin plots with data points
library(ggResidpanel) # for model assumption plots
library(kableExtra) # nice tables that can scroll
library(pander) # more nice tables
library(stringr) # helps build functions
library(forcats) # for changing the order of factors
library(groupdata2) # for assigning rows in data-frames to groups
# Read in data frame and add pipette tip column
all_data <- read.csv("mtDNA_larval_competition_data.csv") %>%
arrange(Individual) %>%
mutate(duplicate = str_extract(Strain, "[:digit:]")) %>%
group(n = 2, method = "greedy") %>% rename(Pipette_tip = .groups)
# Create a function for standard error - generally useful and needed for later
SE <- function(x) sd(x)/sqrt(length(x))
# helper for saving stuff and naming the file object.rds
save_it <- function(object){
saveRDS(get(object), file = paste(object, ".rds", sep = ""))}
# Define a standard dodge for the error bar plots
pd <- position_dodge(0.75) # move them 0.3 to the left and right
# function for finding CIs for binomial data
get_CIs_for_binomial_trials <- function(success, failure){
output <- as.data.frame(matrix(NA, nrow = length(success), ncol = 5))
for(i in 1:length(success)){
n <- success[i] + failure[i]
x <- binom.test(success[i], n)
output[i,] <- c(x$estimate,
as.numeric(x$conf.int),
sqrt(x$estimate * (1-x$estimate)/n), # binomial SE = sqrt(p(1-p)/n)
n)
}
names(output) <- c("Proportion", "lowerCI", "upperCI", "SE", "n")
output
}
# e.g. get_CIs_for_binomial_trials(survived = c(10,100), died = c(50,30))
# Clean the dataset up for analysis
# Select the columns we're interested in and rename them
fitness_data <- dplyr::select(all_data, Individual, Block, duplicate, Pipette_tip, Sex, Focal.haplotype, Social.haplotype, Mortality, Social.Survival, Development.time..hrs., Day.emerged, Hours.from.lights.on, Wing.size..mm., Female.offspring, Male.offspring, Total.female.assay, Total.red.all.vials, Total.bw.all.vials, Proportion.red.all.vials) %>%
rename(Block = Block, Duplicate = duplicate, Day = Day.emerged, Hours = Hours.from.lights.on, Survived = Mortality, Focal_haplotype = Focal.haplotype, Social_haplotype = Social.haplotype, Social_survival = Social.Survival, Dev_time = Development.time..hrs., Wing_length = Wing.size..mm., Maternal_female_offspring = Female.offspring, Maternal_male_offspring = Male.offspring, Maternal_total_offspring = Total.female.assay, Paternal_focal_offspring = Total.red.all.vials, Patneral_bw_offspring = Total.bw.all.vials, Proportion_focal = Proportion.red.all.vials)
# Define new levels for mortality to make renaming possible
levels(fitness_data$Survived) <- c(levels(fitness_data$Survived), "NO")
levels(fitness_data$Survived) <- c(levels(fitness_data$Survived), "YES")
# Rename the mortality responses
# L means died as larva, P means died as pupae, N means did not die (i.e. eclosed as an adult)
fitness_data$Survived[fitness_data$Survived == 'L'] <- 'NO'
fitness_data$Survived[fitness_data$Survived == 'P'] <- 'NO'
fitness_data$Survived[fitness_data$Survived == 'N'] <- 'YES'
# Now that it makes sense change "YES" to 1 and "NO" to 0 so we can fit a binomial GLM.
levels(fitness_data$Survived) <- c(levels(fitness_data$Survived), "1")
levels(fitness_data$Survived) <- c(levels(fitness_data$Survived), "0")
fitness_data$Survived[fitness_data$Survived == "YES"] <- 1
fitness_data$Survived[fitness_data$Survived == "NO"] <- 0
# Make the factor numeric
fitness_data$Survived <- as.numeric(as.character(fitness_data$Survived))
# Create specific datasets for each fitness trait
# Remove all rows that contain an NA value in the survival column. The NAs mean things like the GFP sorting did not work, or the vial was never even set up due to a shortage of larvae. They are not meaningful data, and we remove them here.
survival <- fitness_data %>% filter(!is.na(Survived))
# Remove all rows that contain an NA value in the development time column. This instances represent flies where we failed to measure development time.
larval_development <- fitness_data %>% filter(!is.na(Dev_time))
# Remove all rows that contain an NA value in the wing length column. Wing length was not measured in Blocks 1 and 2.
body_size <- fitness_data %>% filter(!is.na(Wing_length))
# Remove all rows that contain an NA value in the female reproductive output column, and where females did not survive to adulthood (coded as producing 0 offspring).
female_reproductive_output <- fitness_data %>% filter(!is.na(Maternal_total_offspring), Survived == 1)
# Male adult fitness
# First remove females from the dataset.
Male_fitness <- all_data %>% filter(!is.na(Total.red.all.vials))
# Create an offspring counted column so that the data is correctly formatted for a binomial success-failure model.
Male_fitness$Offspring_counted <- Male_fitness$Total.red.all.vials + Male_fitness$Total.bw.all.vials
# Now lets remove vials where the female produced 0 offspring (this includes trials where the male died in development)
Male_fitness <- Male_fitness %>% filter(!(Offspring_counted == 0))
# Select relevant columns and rename variables
Male_fitness <- dplyr::select(Male_fitness, Individual, Block, Pipette_tip, Focal.haplotype, Social.haplotype, Social.Survival, Mortality, Development.time..hrs., Day.emerged, Wing.size..mm., Hours.from.lights.on, Total.red.all.vials, Total.bw.all.vials, Offspring_counted, Proportion.red.all.vials, duplicate) %>%
rename(Focal_male_offspring = Total.red.all.vials, Block = Block, Day = Day.emerged, Hours = Hours.from.lights.on, Survived = Mortality, Focal_haplotype = Focal.haplotype, Social_haplotype = Social.haplotype, Social_survival = Social.Survival, Dev_time = Development.time..hrs., Wing_length = Wing.size..mm., Proportion_focal = Proportion.red.all.vials, Bw_offspring = Total.bw.all.vials, Duplicate = duplicate)
# Create a correlation matrix for male and female life-history traits
Male_cor <- fitness_data %>%
select(Dev_time, Wing_length, Paternal_focal_offspring, Proportion_focal) %>%
rename(Development_time = Dev_time, Offspring_produced = Paternal_focal_offspring, Proportion_offspring_produced = Proportion_focal) %>%
as.data.frame()
Male_cor$Pipette_tip <- as.numeric(as.character(Male_cor$Pipette_tip))
Male_cor <- Male_cor %>% select(-(Pipette_tip))
Female_cor <- fitness_data %>%
filter(!is.na(Survived)) %>%
filter(Sex == "F") %>%
select(Dev_time, Wing_length, Maternal_female_offspring, Maternal_male_offspring) %>%
rename(Development_time = Dev_time, Female_offspring = Maternal_female_offspring, Male_offspring = Maternal_male_offspring) %>% as.data.frame()
Female_cor$Pipette_tip <- as.numeric(as.character(Female_cor$Pipette_tip))
Female_cor <- Female_cor %>% select(-(Pipette_tip))
# Male_correlations <- cor(Male_cor, use = "complete.obs") %>% pander(split.cell = 40, split.table = Inf)
# Female_correlations <- cor(Female_cor, use = "complete.obs") %>% pander(split.cell = 40, split.table = Inf)
We analysed the data using generalised linear mixed models in the lmer package for R.
Fixed effects
For the analysis of fitness traits expressed in both sexes (survival, development time and body size), we are interested in the effect of an individual’s focal mtDNA, the mtDNA of a social competitor, the effect of a social competitors success, and the effect of sex on fitness. To identify these potential effects each model contained the following fixed effects, and interactions where biologically relevant:
Focal haplotype: the mtDNA haplotype that an individual carries.
Social haplotype: the mtDNA haplotype that a social partner during larval development carries.
Social survival: the survival outcome of the social partner.
Sex: is the focal individual female or male? The social partner will always be of the opposite sex to the focal individual.
We also include:
Duplicate: Each haplotype has been introgressed alongside the w1118 nuclear background in two independent duplicates. WIthin each block we ran multiple replicates that were split in two: half used only duplicate one will the other half used only duplicate two. This fixed effect accounts for any nuclear differences that may have arisen between duplicates.
Random effects
Block: accounts for differences in the response variable between experimental blocks (e.g. to variance in temperature or composition of the fly food). In our experiment a Block contained multiple replicates and a replicate was made up of 25 different cells each housing a pair of larvae.
Model evaluation
Each model was evaluated via AICc values using the dredge function, from the Mumin package. There was rarely a single model that was unequivocally the best fit to the data, so we conducted model averaging for the set of models where delta was < 6, as suggested by Symonds and Moussalli (2011). The present study is a planned experiment to measure the effect of mtDNA on fitness, so we derived model estimates from the conditional model averages.
We fit a glm with binomial errors to model survival
The model:
Survived ~ Focal_haplotype * Social_haplotype * Sex + Duplicate + (1|Block) + (1|Pipette_tip)
# Fit the global model
survival_model <- lme4::glmer(Survived ~ Focal_haplotype * Social_haplotype * Sex + factor(Duplicate) + (1|Block) + (1|Pipette_tip), data = survival, family = "binomial", control = glmerControl(optimizer = "Nelder_Mead", optCtrl=list(maxfun=100000)), na.action = na.fail)
Table S1: Evaluation of the survivorship model. All possible models were evaluated from the global model that included a three-way interaction between focal haplotype, social haplotype and social survival, the stand alone fixed effects sex and duplciate, as well as the random factor block. As there was no clear top model, the final model was calculated via model averaging.
# Compare all possible combinations of models (from the global model)
if(file.exists("survival_dredge.rds")){ # If already done, just load the results
survival_dredge <- readRDS("survival_dredge.rds")
} else {survival_dredge <- dredge(survival_model) # If not already done, run all the models and save the results
lapply(c("survival_dredge"), save_it)
}
survival_table <- subset(survival_dredge, delta < 6, recalc.weights = FALSE) %>% as.data.frame()
names(survival_table)[names(survival_table) == "(Intercept)"] <- "Intercept"
names(survival_table)[names(survival_table) == "factor(Duplicate)"] <- "Duplicate"
names(survival_table)[names(survival_table) == "Focal_haplotype"] <- "Focal haplotype"
names(survival_table)[names(survival_table) == "Sex"] <- "Sex"
names(survival_table)[names(survival_table) == "Social_haplotype"] <- "Social haplotype"
names(survival_table)[names(survival_table) == "Focal_haplotype:Sex"] <- "Focal haplotype x Sex"
names(survival_table)[names(survival_table) == "Focal_haplotype:Social_haplotype"] <- "Focal haplotype x Social haplotype"
names(survival_table)[names(survival_table) == "Sex:Social_haplotype"] <- "Social haplotype x Sex"
names(survival_table)[names(survival_table) == "Focal_haplotype:Sex:Social_haplotype"] <- "Focal haplotype x Social haplotype x Sex"
names(survival_table)[names(survival_table) == "df"] <- "Degrees of freedom"
names(survival_table)[names(survival_table) == "logLik"] <- "Log likelihood"
names(survival_table)[names(survival_table) == "AICc"] <- "AICc"
names(survival_table)[names(survival_table) == "delta"] <- "Delta"
names(survival_table)[names(survival_table) == "weight"] <- "Weight"
pander(survival_table, split.cell = 40, split.table = Inf)
| Intercept | Duplicate | Focal haplotype | Sex | Social haplotype | Focal haplotype x Sex | Focal haplotype x Social haplotype | Social haplotype x Sex | Focal haplotype x Social haplotype x Sex | Degrees of freedom | Log likelihood | AICc | Delta | Weight | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2 | -0.09608 | + | NA | NA | NA | NA | NA | NA | NA | 4 | -1301 | 2609 | 0 | 0.3557 |
| 6 | -0.1418 | + | NA | + | NA | NA | NA | NA | NA | 5 | -1300 | 2610 | 1.097 | 0.2055 |
| 4 | -0.0005772 | + | + | NA | NA | NA | NA | NA | NA | 8 | -1297 | 2610 | 1.162 | 0.199 |
| 8 | -0.0453 | + | + | + | NA | NA | NA | NA | NA | 9 | -1297 | 2611 | 2.304 | 0.1124 |
| 10 | -0.1255 | + | NA | NA | + | NA | NA | NA | NA | 8 | -1299 | 2614 | 5.407 | 0.02382 |
| 1 | -0.2129 | NA | NA | NA | NA | NA | NA | NA | NA | 3 | -1304 | 2615 | 5.687 | 0.0207 |
Table 1: Conditional model coefficients, standard error and 95% confidence limits are shown for the survivorship to adulthood averaged model. Bold rows indicate signficant effects.
# average the models with delta < 6
Survival_avg <- model.avg(survival_dredge, subset = delta < 6)
survival_CIs <- confint(model.avg(survival_dredge, subset = delta < 6)) %>% as.data.frame()
survival_estimate <- coefTable(model.avg(survival_dredge, subset = delta < 6)) %>% as.data.frame()
survival_model_avg <- data.frame(survival_estimate, survival_CIs) %>% select(Estimate, Std..Error, X2.5.., X97.5..)
names(survival_model_avg)[names(survival_model_avg) == "Estimate"] <- "Conditional average estimate"
names(survival_model_avg)[names(survival_model_avg) == "Std..Error"] <- "Standard Error"
names(survival_model_avg)[names(survival_model_avg) == "X2.5.."] <- "2.5% Interval"
names(survival_model_avg)[names(survival_model_avg) == "X97.5.."] <- "97.5% Interval"
pander(survival_model_avg, split.cell = 40, split.table = Inf, emphasize.strong.rows = (2))
| Conditional average estimate | Standard Error | 2.5% Interval | 97.5% Interval | |
|---|---|---|---|---|
| (Intercept) | -0.08278 | 0.3146 | -0.6994 | 0.5338 |
| factor(Duplicate)2 | -0.3077 | 0.1113 | -0.5259 | -0.08957 |
| SexM | 0.09071 | 0.09544 | -0.09635 | 0.2778 |
| Focal_haplotypeBrownsville | -0.08159 | 0.151 | -0.3776 | 0.2144 |
| Focal_haplotypeDahomey | 0.07345 | 0.1512 | -0.2228 | 0.3697 |
| Focal_haplotypeIsrael | -0.2627 | 0.1529 | -0.5624 | 0.03701 |
| Focal_haplotypeSweden | -0.2193 | 0.1536 | -0.5204 | 0.0818 |
| Social_haplotypeBrownsville | -0.07158 | 0.1518 | -0.3692 | 0.226 |
| Social_haplotypeDahomey | 0.037 | 0.152 | -0.2608 | 0.3348 |
| Social_haplotypeIsrael | 0.169 | 0.152 | -0.1288 | 0.4669 |
| Social_haplotypeSweden | 0.01623 | 0.1534 | -0.2845 | 0.317 |
# The full average provides a parameter average across all models considered, including ones where the parameter coefficient is set to 0. The conditional average reports coefficents for only the models where the parameter is included.
survival_plot_data <- survival %>%
mutate(Social_survival = replace(as.character(Social_survival), Social_survival == "L", "Died as larva"),
Social_survival = replace(as.character(Social_survival), Social_survival == "P", "Died as pupa"),
Social_survival = replace(as.character(Social_survival), Social_survival == "N", "Survived to adulthood"))
survival_plot_summary <- survival_plot_data %>%
dplyr::group_by(Social_survival) %>%
dplyr::summarise(number_surviving = sum(Survived), number_died = sum(Survived == 0)) %>%
as.data.frame()
survival_CIs <- get_CIs_for_binomial_trials(survival_plot_summary$number_surviving, survival_plot_summary$number_died) %>% rename(Survived = Proportion)
survival_plot_summary <- cbind(survival_plot_summary, survival_CIs)
survival_plot_data %>%
ggplot(aes(x = Social_survival, y = Survived, fill = Social_survival, colour = Social_survival)) +
#geom_quasirandom(data = survival_plot_data, width = 0.5, alpha = 0.5) +
scale_colour_manual(values = c("Died as larva" = "#a50f15", "Died as pupa" = "#fe9929", "Survived to adulthood" = "#41b6c4")) +
geom_point(data = survival_plot_summary, aes(x = Social_survival, y = Survived), size = 3, colour='black') +
geom_errorbar(data = survival_plot_summary, aes(x = Social_survival, ymax = upperCI, ymin = lowerCI, width = 0), colour = "black") +
labs(x = "Survival outcome of social partner", y = "Proportion of larvae surviving to adulthood") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
#**Figure 1:** Survivorship to adulthood is affected by the success of a social partner. Black points show the mean proportion of larvae that successfully eclosed, with 95% confidence limits.
survival_mtDNA_summary <- survival %>%
dplyr::group_by(Focal_haplotype) %>%
dplyr::summarise(number_surviving = sum(Survived), number_died = sum(Survived == 0)) %>%
as.data.frame()
survival_mtDNA_CIs <- get_CIs_for_binomial_trials(survival_mtDNA_summary$number_surviving, survival_mtDNA_summary$number_died) %>% rename(Survived = Proportion)
survival_mtDNA_summary <- cbind(survival_mtDNA_summary, survival_mtDNA_CIs)
survival_mtDNA_summary %>%
ggplot(aes(x = Focal_haplotype, y = Survived, fill = Focal_haplotype, colour = Focal_haplotype)) +
#geom_quasirandom(data = survival_plot_data, width = 0.5, alpha = 0.5) +
#scale_colour_manual(values = c("Barcelona" = "#a50f15", "Brownsville" = "#fe9929", "Dahomey" = "#41b6c4", "Israel" = "#238443" , "Sweden" = "#4a1486")) +
geom_point(data = survival_mtDNA_summary, aes(x = Focal_haplotype, y = Survived), size = 3, colour='black') +
geom_errorbar(data = survival_mtDNA_summary, aes(x = Focal_haplotype, ymax = upperCI, ymin = lowerCI, width = 0), colour = "black") +
labs(x = "mtDNA haplotype", y = "Proportion of larvae surviving to adulthood") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
Figure 1: The black points show the mean proportion of larvae surviving to eclose for each mtDNA haplotype and its 95% confidence limits.
check these confidence intervals
density_development_plot <- ggplot(larval_development)+
stat_density_ridges(aes(x=Dev_time, y = NA, fill = Sex), alpha = 0.7, scale = 12, position = position_nudge(y = -0.5), show.legend = T) +
geom_vline(xintercept = 238, linetype = 2) +
geom_vline(xintercept = 262, linetype = 2) +
geom_vline(xintercept = 286, linetype = 2) +
xlab("Egg-to-adult development time (hours)") +
ylab("Kernel density estimate") +
theme_bw()+
scale_fill_manual(values = c("F" = "#e41a1c", "M" = "#377eb8"), labels = c("Female", "Male")) +
scale_x_continuous(limits = c(220, 310), breaks = c(220, 230, 240, 250, 260, 270, 280, 290, 300, 310)) +
scale_y_discrete(expand = c(.0,0.0))+
theme(panel.spacing = unit(0.1, "lines"),
text = element_text(size=16),
panel.border= element_blank(),
axis.line=element_line(),
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x = element_text(hjust = 0.5, size = 14))
density_development_plot
Figure S2: The distribution of egg-to-adult development time, split by sex. Dashed lines indicate when lights were turned each morning and highlight the relationship between light and eclosion.
The response variable has a trimodal distribution, that can be potentially explained by the lab’s artificial day-night cycle. When the lights turn on at 7am, eclosion is stimulated.
The model:
Dev_time ~ Focal_haplotype * Social_haplotype * Sex + Duplicate + (1|Block) + (1|Pipette_tip)
# Fit the linear model
linear_dev_model <- lmer(Dev_time ~ Focal_haplotype * Social_haplotype * Sex + factor(Duplicate) + (1|Block) + (1|Pipette_tip), larval_development, na.action = na.fail, REML = FALSE)
Lets have a look at model diagnostics
resid_panel(linear_dev_model)
Despite the data being trimodal, the linear model appears to fit the data adequately. The residuals vs fitted plot indicates that the mean and variance share no relationship. The Q-Q Plot shows that points fall off at the extremes, but generally conform to a linear pattern.
Table S2: Evaluation of the development time model. All possible models were evaluated from the global model that included a three-way interaction between focal haplotype, social haplotype and social survival, the stand alone fixed effects sex and duplciate, as well as the random factor block. As there was no clear top model, the final model was calculated via model averaging.
# Use dredge to compare all possible models derived from the global model
Dev_time_linear_dredge <- dredge(linear_dev_model, extra = "R^2")
development_table <- subset(Dev_time_linear_dredge, delta < 6, recalc.weights = FALSE) %>% as.data.frame()
names(development_table)[names(development_table) == "(Intercept)"] <- "Intercept"
names(development_table)[names(development_table) == "(factor(Duplicate))"] <- "Duplicate"
names(development_table)[names(development_table) == "Focal_haplotype"] <- "Focal haplotype"
names(development_table)[names(development_table) == "Social_haplotype"] <- "Social haplotype"
names(development_table)[names(development_table) == "Focal_haplotype:Sex"] <- "Focal haplotype x Sex"
names(development_table)[names(development_table) == "Focal_haplotype:Social_haplotype"] <- "Focal haplotype x Social haplotype"
names(development_table)[names(development_table) == "Sex:Social_haplotype"] <- "Social haplotype x Sex"
names(development_table)[names(development_table) == "Focal_haplotype:Sex:Social_haplotype"] <- "Focal haplotype x Social haplotype x Sex"
names(development_table)[names(development_table) == "df"] <- "Degrees of freedom"
names(development_table)[names(development_table) == "logLik"] <- "Log likelihood"
names(development_table)[names(development_table) == "AICc"] <- "AICc"
names(development_table)[names(development_table) == "delta"] <- "Delta"
names(development_table)[names(development_table) == "weight"] <- "Weight"
pander(development_table, split.cell = 40, split.table = Inf)
| Intercept | factor(Duplicate) | Focal haplotype | Sex | Social haplotype | Focal haplotype x Sex | Focal haplotype x Social haplotype | Social haplotype x Sex | Focal haplotype x Social haplotype x Sex | R^2 | Degrees of freedom | Log likelihood | AICc | Delta | Weight | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6 | 261.1 | + | NA | + | NA | NA | NA | NA | NA | 0.1235 | 6 | -2998 | 6007 | 0 | 0.3603 |
| 5 | 260.6 | NA | NA | + | NA | NA | NA | NA | NA | 0.1207 | 5 | -2999 | 6008 | 0.296 | 0.3108 |
| 8 | 262.5 | + | + | + | NA | NA | NA | NA | NA | 0.1299 | 10 | -2995 | 6010 | 2.679 | 0.09438 |
| 7 | 261.9 | NA | + | + | NA | NA | NA | NA | NA | 0.1272 | 9 | -2996 | 6010 | 2.945 | 0.08266 |
| 2 | 262.3 | + | NA | NA | NA | NA | NA | NA | NA | 0.116 | 5 | -3001 | 6012 | 4.305 | 0.04186 |
| 1 | 261.7 | NA | NA | NA | NA | NA | NA | NA | NA | 0.1132 | 4 | -3002 | 6012 | 4.651 | 0.03522 |
Table 2: Conditional model coefficients, standard error and 95% confidence limits are shown for the egg-to-adult development time averaged model. Bold rows indicate signficant effects.
# Model averaging
Dev_time_avg <- (model.avg(Dev_time_linear_dredge, subset = delta < 6))
Dev_CIs <- confint(model.avg(Dev_time_linear_dredge, subset = delta < 6)) %>% as.data.frame()
Dev_estimate <- coefTable(model.avg(Dev_time_linear_dredge, subset = delta < 6)) %>% as.data.frame()
Dev_model_avg <- data.frame(Dev_estimate, Dev_CIs) %>% select(Estimate, Std..Error, X2.5.., X97.5..)
names(Dev_model_avg)[names(Dev_model_avg) == "Estimate"] <- "Conditional average estimate"
names(Dev_model_avg)[names(Dev_model_avg) == "Std..Error"] <- "Standard Error"
names(Dev_model_avg)[names(Dev_model_avg) == "X2.5.."] <- "2.5% Interval"
names(Dev_model_avg)[names(Dev_model_avg) == "X97.5.."] <- "97.5% Interval"
pander(Dev_model_avg, split.cell = 40, split.table = Inf, emphasize.strong.rows = 3)
| Conditional average estimate | Standard Error | 2.5% Interval | 97.5% Interval | |
|---|---|---|---|---|
| (Intercept) | 261.2 | 2.39 | 256.5 | 265.9 |
| factor(Duplicate)2 | -1.71 | 1.119 | -3.904 | 0.4842 |
| SexM | 2.247 | 0.8919 | 0.4993 | 3.996 |
| Focal_haplotypeBrownsville | -1.928 | 1.449 | -4.767 | 0.9115 |
| Focal_haplotypeDahomey | -2.71 | 1.416 | -5.486 | 0.06589 |
| Focal_haplotypeIsrael | -1.917 | 1.502 | -4.86 | 1.026 |
| Focal_haplotypeSweden | -0.09253 | 1.511 | -3.054 | 2.869 |
larval_development_plot_data <- larval_development %>%
mutate(Social_survival = replace(as.character(Social_survival), Social_survival == "L", "Died as larva"),
Social_survival = replace(as.character(Social_survival), Social_survival == "P", "Died as pupa"),
Social_survival = replace(as.character(Social_survival), Social_survival == "N", "Survived to adulthood"),
Sex = replace(as.character(Sex), Sex == "F", "Female"),
Sex = replace(as.character(Sex), Sex == "M", "Male"))
larval_development_summary <- larval_development_plot_data %>%
dplyr::group_by(Social_survival, Sex) %>%
dplyr::summarise(Mean_Dev_time = mean(Dev_time), Lower = (Mean_Dev_time - SE(Dev_time)* 1.96), Upper = (Mean_Dev_time + SE(Dev_time)*1.96), n = n()) %>% rename(Dev_time = Mean_Dev_time)
larval_development_plot_data %>%
ggplot(aes(x = Social_survival, y = Dev_time, fill = Social_survival, colour = Social_survival)) +
geom_quasirandom(data = larval_development_plot_data, width = 0.3, size = 2, alpha = 0.5) +
scale_colour_manual(values = c("Died as larva" = "#a50f15", "Died as pupa" = "#fe9929", "Survived to adulthood" = "#41b6c4")) +
geom_point(data = larval_development_summary, aes(x = Social_survival, y = Dev_time), size = 3, colour='black') +
geom_errorbar(data = larval_development_summary, aes(x = Social_survival, ymax = Upper, ymin = Lower, width = 0), colour = "black") +
geom_hline(yintercept = c(238, 262, 286), linetype = 2, colour = "grey", alpha = 0.5) +
facet_wrap(~ Sex) +
labs(x = "Survival outcome of social partner", y = "Egg-to-adult development time (hrs)") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
# **Figure 3:** Egg-to-adult development time is affected by an individual's sex and the success of a social competitor. The coloured points show the development time for individual flies. The black points show the mean development time for males and females and its 95% confidence limits. Dashed lines indicate when lights were turned each morning and highlight the relationship between light and eclosion.
larval_development_plot_data <- larval_development %>%
mutate(Sex = replace(as.character(Sex), Sex == "F", "Female"),
Sex = replace(as.character(Sex), Sex == "M", "Male"))
development_mtDNA_summary <- larval_development_plot_data %>%
dplyr::group_by(Focal_haplotype) %>%
dplyr::summarise(Mean_Dev_time = mean(Dev_time), Lower = (Mean_Dev_time - SE(Dev_time)* 1.96), Upper = (Mean_Dev_time + SE(Dev_time)*1.96), n = n()) %>% rename(Dev_time = Mean_Dev_time)
larval_development_plot_data %>%
ggplot(aes(x = Focal_haplotype, y = Dev_time, fill = Focal_haplotype, colour = Focal_haplotype)) +
geom_quasirandom(data = larval_development_plot_data, width = 0.3, size = 2, alpha = 0.5) +
scale_colour_manual(values = c("Barcelona" = "#a50f15", "Brownsville" = "#fe9929", "Dahomey" = "#41b6c4", "Israel" = "#238443" , "Sweden" = "#4a1486")) +
geom_point(data = development_mtDNA_summary, aes(x = Focal_haplotype, y = Dev_time), size = 3, colour='black') +
geom_errorbar(data = development_mtDNA_summary, aes(x = Focal_haplotype, ymax = Upper, ymin = Lower, width = 0), colour = "black") +
geom_hline(yintercept = c(238, 262, 286), linetype = 2, colour = "grey", alpha = 0.5) +
labs(x = "mtDNA haplotype", y = "Egg-to-adult development time (hrs)") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank())
Figure 2: Egg-to-adult development time is affected by an individual’s mtDNA haplotype. The coloured points show the development time for individual flies. The black points show the mean development time for males and females and its 95% confidence limits.
We use wing length as a proxy for adult body size. Errors are normally distributed, therefore we fit a linear mixed model.
The model:
Wing_length ~ Focal_haplotype * Social_haplotype * Sex + Duplicate + (1|Block) + (1|Pipette_tip)
body_size_model<- lmer(Wing_length ~ Focal_haplotype * Social_haplotype * Sex + factor(Duplicate) + (1|Block) + (1|Pipette_tip), body_size, na.action = na.fail, REML = FALSE)
Table S3: Evaluation of the wing length model. All possible models were evaluated from the global model that included a three-way interaction between focal haplotype, social haplotype and social survival, the standalone fixed effects sex and duplicate, as well as the random factor ‘Block’. As there was no clear top model, the final model was calculated via model averaging.
# Compare all possible combinations of models (from the global model)
body_size_dredge <- dredge(body_size_model)
size_table <- subset(body_size_dredge, delta < 6, recalc.weights = FALSE) %>% as.data.frame()
names(size_table)[names(size_table) == "(Intercept)"] <- "Intercept"
names(size_table)[names(size_table) == "factor(Duplicate)"] <- "Duplicate"
names(size_table)[names(size_table) == "Focal_haplotype"] <- "Focal haplotype"
names(size_table)[names(size_table) == "Sex"] <- "Sex"
names(size_table)[names(size_table) == "Social_haplotype"] <- "Social haplotype"
names(size_table)[names(size_table) == "Focal_haplotype:Sex"] <- "Focal haplotype x Sex"
names(size_table)[names(size_table) == "Focal_haplotype:Social_haplotype"] <- "Focal haplotype x Social haplotype"
names(size_table)[names(size_table) == "Sex:Social_haplotype"] <- "Social haplotype x Sex"
names(size_table)[names(size_table) == "Focal_haplotype:Sex:Social_haplotype"] <- "Focal haplotype x Social haplotype x Sex"
names(size_table)[names(size_table) == "df"] <- "Degrees of freedom"
names(size_table)[names(size_table) == "logLik"] <- "Log likelihood"
names(size_table)[names(size_table) == "AICc"] <- "AICc"
names(size_table)[names(size_table) == "delta"] <- "Delta"
names(size_table)[names(size_table) == "weight"] <- "Weight"
pander(size_table, split.cell = 40, split.table = Inf)
| Intercept | Duplicate | Focal haplotype | Sex | Social haplotype | Focal haplotype x Sex | Focal haplotype x Social haplotype | Social haplotype x Sex | Focal haplotype x Social haplotype x Sex | Degrees of freedom | Log likelihood | AICc | Delta | Weight | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 5 | 1.063 | NA | NA | + | NA | NA | NA | NA | NA | 5 | 440.6 | -871 | 0 | 0.6733 |
| 6 | 1.063 | + | NA | + | NA | NA | NA | NA | NA | 6 | 440.6 | -869 | 2.019 | 0.2454 |
Table 3: Conditional model coefficients, standard error and 95% confidence limits are shown for the wing length averaged model. Bold rows indicate signficant effects.
# Model averaging
#summary(model.avg(body_size_dredge, subset = delta < 6))
Size_CIs <- confint(model.avg(body_size_dredge, subset = delta < 6)) %>% as.data.frame()
Size_estimate <- coefTable(model.avg(body_size_dredge, subset = delta < 6)) %>% as.data.frame()
Size_model_avg <- data.frame(Size_estimate, Size_CIs) %>% select(Estimate, Std..Error, X2.5.., X97.5..)
names(Size_model_avg)[names(Size_model_avg) == "Estimate"] <- "Conditional average estimate"
names(Size_model_avg)[names(Size_model_avg) == "Std..Error"] <- "Standard Error"
names(Size_model_avg)[names(Size_model_avg) == "X2.5.."] <- "2.5% Interval"
names(Size_model_avg)[names(Size_model_avg) == "X97.5.."] <- "97.5% Interval"
pander(Size_model_avg, split.cell = 40, split.table = Inf, emphasize.strong.rows = (2))
| Conditional average estimate | Standard Error | 2.5% Interval | 97.5% Interval | |
|---|---|---|---|---|
| (Intercept) | 1.063 | 0.0156 | 1.032 | 1.093 |
| SexM | -0.08628 | 0.007203 | -0.1004 | -0.07216 |
| factor(Duplicate)2 | -0.002049 | 0.01004 | -0.02173 | 0.01763 |
body_size_plot_data <- body_size %>%
mutate(Social_survival = replace(as.character(Social_survival), Social_survival == "L", "Died as larva"),
Social_survival = replace(as.character(Social_survival), Social_survival == "P", "Died as pupa"),
Social_survival = replace(as.character(Social_survival), Social_survival == "N", "Survived to adulthood"),
Sex = replace(as.character(Sex), Sex == "F", "Female"),
Sex = replace(as.character(Sex), Sex == "M", "Male"))
body_size_summary <- body_size_plot_data %>%
dplyr::group_by(Sex) %>%
dplyr::summarise(Mean_wing_length = mean(Wing_length), Lower = (Mean_wing_length - SE(Wing_length)* 1.96), Upper = (Mean_wing_length + SE(Wing_length)*1.96), n = n()) %>% rename(Wing_length = Mean_wing_length)
body_size_plot_data %>%
ggplot(aes(x = Sex, y = Wing_length, fill = Sex, colour = Sex)) +
geom_quasirandom(data = body_size_plot_data, width = 0.3, size = 2, alpha = 0.5) +
scale_colour_manual(values = c("Female" = "#fe9929", "Male" = "#41b6c4")) +
geom_point(data = body_size_summary, aes(x = Sex, y = Wing_length), size = 3, colour='black') +
geom_errorbar(data = body_size_summary, aes(x = Sex, ymax = Upper, ymin = Lower, width = 0), colour = "black") +
labs(x = "Sex", y = "Wing length (mm)") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
Figure 5: Sex affects wing length. The coloured points show the development time for individual flies. The black points show the mean wing length for males and females and its 95% confidence limits.
To effectively accommodate zero-inflation, we modelled female offspring production using the glmmTMB package (Brooks et al. 2017). This package allows us to fit hurdle models and zero-inflated models.
Hurdle models treat zero-count and nonzero outcomes as two completely separate categories, while zero-inflated models treat zero-count outcomes as a mixture of structural and sampling zeros.
We analysed the number of offspring produced by females using a hurdle model with negative binomial errors. This approach allowed us to answer two questions: (1) did mtDNA and/or competition affect the incidence of failing to produce any offspring? and (2) for females that produced at least one offspring, was the number of offspring produced affected by mtDNA/competition?
The model:
Maternal_total_offspring ~ Focal_haplotype * Social_haplotype + factor(Duplicate) + (1|Block)
female_hurdle_model <- glmmTMB(Maternal_total_offspring ~ Focal_haplotype * Social_haplotype + factor(Duplicate) + (1|Block), data = female_reproductive_output, family = list(family="truncated_nbinom1",link="log"), ziformula = ~., na.action = na.fail, REML = FALSE)
Table S4: Evaluation of the female reproductive output model. All possible models were evaluated from the global model that included an interaction between focal haplotype and social haplotype, the standalone fixed effect ‘duplicate’, and the random factor ‘Block’. As there was no clear top model, the final model was calculated via model averaging. The zero-inflated results correspond to question (1), while the conditional results correspond to question (2) above.
# Compare all possible combinations of models (from the global model)
if(file.exists("female_dredge.rds")){ # If already done, just load the results
female_dredge <- readRDS("female_dredge.rds")
} else {female_dredge <- dredge(female_hurdle_model) # If not already done, run all the models and save the results
lapply(c("female_dredge"), save_it)
}
female_table <- subset(female_dredge, delta < 6, recalc.weights = FALSE) %>% as.data.frame()
names(female_table)[names(female_table) == "cond((Int))"] <- "Conditional intercept"
names(female_table)[names(female_table) == "zi((Int))"] <- "Zero-inflated intercept"
names(female_table)[names(female_table) == "disp((Int))"] <- "Dispersion factor intercept"
names(female_table)[names(female_table) == "cond(factor(Duplicate))"] <- "Conditional (Duplicate)"
names(female_table)[names(female_table) == "cond(Focal_haplotype)"] <- "Conditional (Focal haplotype)"
names(female_table)[names(female_table) == "cond(Social_haplotype)"] <- "Conditional (Social haplotype)"
names(female_table)[names(female_table) == "cond(Focal_haplotype:Social_haplotype)"] <- "Conditional (Focal haplotype x Social haplotype)"
names(female_table)[names(female_table) == "zi(factor(Duplicate))"] <- "Zero-inflated (Duplicate)"
names(female_table)[names(female_table) == "zi(Focal_haplotype)"] <- "Zero-inflated (Focal haplotype)"
names(female_table)[names(female_table) == "zi(Social_haplotype)"] <- "Zero-inflated (Social haplotype)"
names(female_table)[names(female_table) == "zi(Focal_haplotype:Social_haplotype)"] <- "Zero-inflated (Focal haplotype x Social haplotype)"
names(female_table)[names(female_table) == "df"] <- "Degrees of freedom"
names(female_table)[names(female_table) == "logLik"] <- "Log likelihood"
names(female_table)[names(female_table) == "AICc"] <- "AICc"
names(female_table)[names(female_table) == "delta"] <- "Delta"
names(female_table)[names(female_table) == "weight"] <- "Weight"
pander(female_table, split.cell = 40, split.table = Inf)
| Conditional intercept | Zero-inflated intercept | Dispersion factor intercept | Conditional (Duplicate) | Conditional (Focal haplotype) | Conditional (Social haplotype) | Conditional (Focal haplotype x Social haplotype) | Zero-inflated (Duplicate) | Zero-inflated (Focal haplotype) | Zero-inflated (Social haplotype) | Zero-inflated (Focal haplotype x Social haplotype) | Degrees of freedom | Log likelihood | AICc | Delta | Weight | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 83 | 3.932 | -1.398 | + | NA | + | NA | NA | + | NA | + | NA | 14 | -1545 | 3119 | 0 | 0.2825 |
| 67 | 3.932 | -1.245 | + | NA | + | NA | NA | NA | NA | + | NA | 13 | -1546 | 3120 | 1.221 | 0.1534 |
| 84 | 3.921 | -1.398 | + | + | + | NA | NA | + | NA | + | NA | 15 | -1545 | 3120 | 1.842 | 0.1125 |
| 19 | 3.932 | -0.9606 | + | NA | + | NA | NA | + | NA | NA | NA | 10 | -1551 | 3122 | 2.961 | 0.06427 |
| 81 | 3.839 | -1.398 | + | NA | NA | NA | NA | + | NA | + | NA | 10 | -1551 | 3122 | 3.05 | 0.06149 |
| 68 | 3.921 | -1.245 | + | + | + | NA | NA | NA | NA | + | NA | 14 | -1546 | 3122 | 3.053 | 0.06138 |
| 82 | 3.821 | -1.398 | + | + | NA | NA | NA | + | NA | + | NA | 11 | -1550 | 3123 | 4.266 | 0.03348 |
| 65 | 3.839 | -1.245 | + | NA | NA | NA | NA | NA | NA | + | NA | 9 | -1552 | 3123 | 4.313 | 0.0327 |
| 20 | 3.921 | -0.9606 | + | + | + | NA | NA | + | NA | NA | NA | 11 | -1550 | 3123 | 4.762 | 0.02612 |
| 115 | 3.932 | -1.31 | + | NA | + | NA | NA | + | + | + | NA | 18 | -1543 | 3124 | 5.306 | 0.0199 |
| 66 | 3.821 | -1.245 | + | + | NA | NA | NA | NA | NA | + | NA | 10 | -1552 | 3124 | 5.518 | 0.0179 |
| 3 | 3.932 | -0.783 | + | NA | + | NA | NA | NA | NA | NA | NA | 9 | -1553 | 3124 | 5.56 | 0.01753 |
| 99 | 3.932 | -1.156 | + | NA | + | NA | NA | NA | + | + | NA | 17 | -1545 | 3125 | 5.932 | 0.01455 |
Table 4: Conditional (after hurdle) and zi (zero-hurdle requirement) model coefficients, standard error and 95% confidence limits are shown for the female offspring production averaged model. Bold rows indicate signficant effects.
#summary(model.avg(female_dredge, subset = delta < 6))
Female_CIs <- confint(model.avg(female_dredge, subset = delta < 6)) %>% as.data.frame()
Female_estimate <- coefTable(model.avg(female_dredge, subset = delta < 6)) %>% as.data.frame()
Female_model_avg <- data.frame(Female_estimate, Female_CIs) %>% select(Estimate, Std..Error, X2.5.., X97.5..)
names(Female_model_avg)[names(Female_model_avg) == "Estimate"] <- "Conditional average estimate"
names(Female_model_avg)[names(Female_model_avg) == "Std..Error"] <- "Standard Error"
names(Female_model_avg)[names(Female_model_avg) == "X2.5.."] <- "2.5% Interval"
names(Female_model_avg)[names(Female_model_avg) == "X97.5.."] <- "97.5% Interval"
pander(Female_model_avg, split.cell = 40, split.table = Inf, emphasize.strong.rows = c(2, 5, 10))
| Conditional average estimate | Standard Error | 2.5% Interval | 97.5% Interval | |
|---|---|---|---|---|
| cond((Int)) | 3.914 | 0.07512 | 3.766 | 4.061 |
| cond(Focal_haplotypeBrownsville) | -0.1902 | 0.07958 | -0.3462 | -0.03426 |
| cond(Focal_haplotypeDahomey) | -0.08379 | 0.07628 | -0.2333 | 0.06572 |
| cond(Focal_haplotypeIsrael) | -0.005715 | 0.08053 | -0.1635 | 0.1521 |
| cond(Focal_haplotypeSweden) | -0.212 | 0.08357 | -0.3758 | -0.04823 |
| zi((Int)) | -1.291 | 0.303 | -1.885 | -0.6972 |
| zi(factor(Duplicate)2) | 0.4127 | 0.221 | -0.02053 | 0.8459 |
| zi(Social_haplotypeBrownsville) | 0.5457 | 0.3595 | -0.159 | 1.25 |
| zi(Social_haplotypeDahomey) | 0.1975 | 0.3541 | -0.4966 | 0.8916 |
| zi(Social_haplotypeIsrael) | 1.028 | 0.3361 | 0.3692 | 1.687 |
| zi(Social_haplotypeSweden) | 0.396 | 0.3628 | -0.3151 | 1.107 |
| cond(factor(Duplicate)2) | 0.0361 | 0.05763 | -0.07684 | 0.149 |
| zi(Focal_haplotypeBrownsville) | 0.01505 | 0.3265 | -0.6249 | 0.655 |
| zi(Focal_haplotypeDahomey) | -0.2685 | 0.334 | -0.9232 | 0.3862 |
| zi(Focal_haplotypeIsrael) | 0.2045 | 0.328 | -0.4384 | 0.8473 |
| zi(Focal_haplotypeSweden) | -0.3775 | 0.3652 | -1.093 | 0.3383 |
female_zi_plot_data <- female_reproductive_output %>%
mutate(Binary_maternal_offspring = ifelse(Maternal_total_offspring > 0, "1", "0"))
female_zi_summary <- female_zi_plot_data %>%
dplyr::group_by(Social_haplotype) %>%
dplyr::summarise(number_producing_offspring = sum(Binary_maternal_offspring == 1), number_zero_offspring = sum(Binary_maternal_offspring == 0)) %>%
as.data.frame()
female_zi_CIs <- get_CIs_for_binomial_trials(female_zi_summary$number_producing_offspring, female_zi_summary$number_zero_offspring) %>% rename(Binary_maternal_offspring = Proportion)
female_zi_summary <- cbind(female_zi_summary, female_zi_CIs)
female_zi_plot_data %>%
ggplot(aes(x = Social_haplotype, y = Binary_maternal_offspring, fill = Social_haplotype, colour = Social_haplotype)) +
geom_point(data = female_zi_summary, aes(x = Social_haplotype, y = Binary_maternal_offspring), size = 3, colour='black') +
geom_errorbar(data = female_zi_summary, aes(x = Social_haplotype, ymax = upperCI, ymin = lowerCI, width = 0), colour = "black") +
labs(x = "Social male mtDNA haplotype", y = "Proportion of females producing offspring") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
Figure 6: The proportion of females successfully producing offspring is affected by the mtDNA of a social male competitor during larval development. Black points show the mean for each social haplotype and associated confidence intervals. Data corresponds to the hurdle (binomial) component of the hurdle model.
female_cond_plot_data <- female_reproductive_output %>%
mutate(Social_survival = replace(as.character(Social_survival), Social_survival == "L", "Died as larva"),
Social_survival = replace(as.character(Social_survival), Social_survival == "P", "Died as pupa"),
Social_survival = replace(as.character(Social_survival), Social_survival == "N", "Survived to adulthood")) %>%
filter(Maternal_total_offspring != 0)
female_cond_summary <- female_cond_plot_data %>%
dplyr::group_by(Focal_haplotype) %>%
dplyr::summarise(Mean_offspring = mean(Maternal_total_offspring), Lower = (Mean_offspring - SE(Maternal_total_offspring)* 1.96), Upper = (Mean_offspring + SE(Maternal_total_offspring)*1.96), n = n()) %>% rename(Maternal_total_offspring = Mean_offspring)
female_cond_plot_data %>%
ggplot(aes(x = Focal_haplotype, y = Maternal_total_offspring, fill = Focal_haplotype, colour = Focal_haplotype)) +
geom_quasirandom(data = female_cond_plot_data, width = 0.3, size = 2, alpha = 0.5) +
scale_colour_manual(values = c("Barcelona" = "#a50f15", "Brownsville" = "#fe9929", "Dahomey" = "#41b6c4", "Israel" = "#238443" , "Sweden" = "#4a1486")) +
geom_point(data = female_cond_summary, aes(x = Focal_haplotype, y = Maternal_total_offspring), size = 3, colour='black') +
geom_errorbar(data = female_cond_summary, aes(x = Focal_haplotype, ymax = Upper, ymin = Lower, width = 0), colour = "black") +
labs(x = "Female mtDNA haplotype", y = "Number of offspring produced") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
Figure 7: Number of offspring produced by females that produced at least one offspring, split by mitochondrial haplotype. Data corresponds to the conditional component of the hurdle model. Coloured points show the number of offspring produced by individual females. The black points show the mean reproductive output for females and its 95% confidence limits.
We follow the classic approach to sperm competition analysis and consider male fitness as the proportion of offspring sired by an experimental mitoline male while competing against a standard bw male.
Here we are measuring male fitness as 1) the ability of a male to inseminate a female in the presence of another male and 2) the competitive ability of his sperm within females that have been inseminated by another male.
As shown below, the data contains many 0 or 1 values - corresponding to a monopoly of female fertilisation by one of the males. We could assume the data are binomial, and class any non-zero values as ‘1’. Alternatively, we could specify a beta-binomial distribution, which allows us to model the data in its current form, with one exception. The beta-binomial family is used to model data that falls between 0-1, which is perfect for our proportional data. However, this family does not account for values exactly equal to 0 or 1. Therefore, I add one offspring to the count of each vial for each phenotype, thereby removing all vials where one male sired all the offspring in the vial. This allows us to effectively model the data, without substantial changes to the raw data.
density_male_plot <- ggplot(Male_fitness)+
stat_density_ridges(aes(x=Proportion_focal, y = NA), alpha = 0.7, scale = 12, position = position_nudge(y = -0.5), show.legend = T) +
xlab("Proportion of offspring sired by experimental male") +
ylab("Kernel density estimate") +
theme_bw()+
scale_x_continuous(limits = c(0, 1)) +
theme(panel.spacing = unit(0.1, "lines"),
text = element_text(size=16),
panel.border= element_blank(),
axis.line=element_line(),
panel.grid.major.x = element_blank(),
panel.grid.major.y = element_blank(),
panel.grid.minor.y = element_blank(),
panel.grid.minor.x = element_blank(),
axis.text.y=element_blank(),
axis.ticks.y=element_blank(),
axis.title.x = element_text(hjust = 0.5, size = 14))
density_male_plot
The Brownsville haplotype renders males sterile alongside the w1118 nuclear background and sub-fertile alongside all other tested backgrounds. In our experiment, we find that Brownsville males are able to produce offspring but to a very limited capacity. Due to this, our model will not converge with the Brownsville males in the dataset. Therefore, we acknowledge that there is an effect of the Brownsville focal haplotype on male fitness and then remove it from the dataset.
We transform the data to binary and fit the model:
(Focal_male_offspring, bw_offspring) ~ Focal_haplotype * Social_haplotype + Duplicate + (1|Block)
Binary_male_fitness <- Male_fitness %>%
filter(Focal_haplotype != "Brownsville") %>%
mutate(Binary_paternal_offspring = ifelse(Proportion_focal > 0, "1", "0"))
Binary_male_model <- lme4::glmer(factor(Binary_paternal_offspring) ~ Focal_haplotype * Social_haplotype + factor(Duplicate) + (1|Block), data = Binary_male_fitness, family = "binomial", control = glmerControl(optimizer = "Nelder_Mead", optCtrl=list(maxfun=100000)), na.action = na.fail)
Table S4: Evaluation of the male adult fitness model, where data was transformed to a binary format. All possible models were evaluated from the global model that included an interaction between focal haplotype and social haplotype, the standalone fixed effect ‘duplicate’, and the random factors ‘Block’. As there was no clear top model, the final model was calculated via model averaging.
male_binary_dredge <- dredge(Binary_male_model)
Male_binary_table <- subset(male_binary_dredge, delta < 6, recalc.weights = FALSE) %>% as.data.frame()
names(Male_binary_table)[names(Male_binary_table) == "df"] <- "Degrees of freedom"
names(Male_binary_table)[names(Male_binary_table) == "logLik"] <- "Log likelihood"
names(Male_binary_table)[names(Male_binary_table) == "AICc"] <- "AICc"
names(Male_binary_table)[names(Male_binary_table) == "delta"] <- "Delta"
names(Male_binary_table)[names(Male_binary_table) == "weight"] <- "Weight"
pander(Male_binary_table, split.cell = 40, split.table = Inf)
| (Intercept) | factor(Duplicate) | Focal_haplotype | Social_haplotype | Focal_haplotype:Social_haplotype | Degrees of freedom | Log likelihood | AICc | Delta | Weight | |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 0.3449 | NA | NA | NA | NA | 2 | -197.4 | 398.8 | 0 | 0.4916 |
| 2 | 0.3033 | + | NA | NA | NA | 3 | -197.3 | 400.6 | 1.801 | 0.1998 |
| 5 | 0.6008 | NA | NA | + | NA | 6 | -194.6 | 401.5 | 2.669 | 0.1294 |
| 3 | 0.3757 | NA | + | NA | NA | 5 | -196.2 | 402.6 | 3.829 | 0.07246 |
| 6 | 0.5422 | + | NA | + | NA | 7 | -194.4 | 403.2 | 4.401 | 0.05445 |
| 4 | 0.3386 | + | + | NA | NA | 6 | -196.1 | 404.5 | 5.716 | 0.02821 |
Table 5: Model coefficients, standard error and 95% confidence limits are shown for the binary male adult fitness averaged model. Bold rows indicate signficant effects.
#summary(model.avg(male_binary_dredge, subset = delta < 6))
Male_binary_CIs <- confint(model.avg(male_binary_dredge, subset = delta < 6)) %>% as.data.frame()
Male_binary_estimate <- coefTable(model.avg(male_binary_dredge, subset = delta < 6)) %>% as.data.frame()
Male_binary_model_avg <- data.frame(Male_binary_estimate, Male_binary_CIs) %>% select(Estimate, Std..Error, X2.5.., X97.5..)
names(Male_binary_model_avg)[names(Male_binary_model_avg) == "Estimate"] <- "Conditional average estimate"
names(Male_binary_model_avg)[names(Male_binary_model_avg) == "Std..Error"] <- "Standard Error"
names(Male_binary_model_avg)[names(Male_binary_model_avg) == "X2.5.."] <- "2.5% Interval"
names(Male_binary_model_avg)[names(Male_binary_model_avg) == "X97.5.."] <- "97.5% Interval"
pander(Male_binary_model_avg, split.cell = 40, split.table = Inf)
| Conditional average estimate | Standard Error | 2.5% Interval | 97.5% Interval | |
|---|---|---|---|---|
| (Intercept) | 0.3835 | 0.2505 | -0.1075 | 0.8744 |
| factor(Duplicate)2 | 0.1338 | 0.2648 | -0.3852 | 0.6528 |
| Social_haplotypeBrownsville | -0.7255 | 0.3805 | -1.471 | 0.02038 |
| Social_haplotypeDahomey | -0.1431 | 0.4016 | -0.9303 | 0.6441 |
| Social_haplotypeIsrael | -0.2982 | 0.3942 | -1.071 | 0.4743 |
| Social_haplotypeSweden | 0.03149 | 0.4098 | -0.7717 | 0.8346 |
| Focal_haplotypeDahomey | -0.2619 | 0.3213 | -0.8916 | 0.3678 |
| Focal_haplotypeIsrael | -0.04169 | 0.3477 | -0.7233 | 0.6399 |
| Focal_haplotypeSweden | 0.2594 | 0.354 | -0.4344 | 0.9532 |
male_binary_plot_data <- Male_fitness %>%
mutate(Binary_paternal_offspring = ifelse(Focal_male_offspring > 0, "1", "0"))
male_binary_summary <- male_binary_plot_data %>%
dplyr::group_by(Social_haplotype) %>%
dplyr::summarise(number_producing_offspring = sum(Binary_paternal_offspring == 1), number_zero_offspring = sum(Binary_paternal_offspring == 0)) %>%
as.data.frame()
male_binary_CIs <- get_CIs_for_binomial_trials(male_binary_summary$number_producing_offspring, male_binary_summary$number_zero_offspring) %>% rename(Binary_paternal_offspring = Proportion)
male_binary_summary <- cbind(male_binary_summary, male_binary_CIs)
male_binary_plot_data %>%
ggplot(aes(x = Social_haplotype, y = Binary_paternal_offspring, fill = Social_haplotype, colour = Social_haplotype)) +
geom_point(data = male_binary_summary, aes(x = Social_haplotype, y = Binary_paternal_offspring), size = 3, colour='black') +
geom_errorbar(data = male_binary_summary, aes(x = Social_haplotype, ymax = upperCI, ymin = lowerCI, width = 0), colour = "black") +
labs(x = "Social female mtDNA haplotype", y = "Proportion of males producing offspring") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
Figure 8: The proportion of males successfully producing offspring is not affected by the mtDNA of a social female competitor during larval development. Black points show the mean for each social haplotype and associated confidence intervals.
Beta-binomial model:
We can also use the beta binomial distribution to model our data. However, this distribution can’t handle 0 or 1 values so we add 1 to each offspring count (offspring produced by mitoline and competitor males) in each vial.
(Focal_male_offspring, bw_offspring) ~ Focal_haplotype * Social_haplotype + Duplicate + (1|Block)
Male_fitness_without_Brownsville <- Male_fitness %>%
filter(Focal_haplotype != "Brownsville") %>%
mutate(Individual = 1:n()) %>%
mutate(Focal_male_offspring_beta = Focal_male_offspring + 1) %>%
mutate(Bw_offspring_beta = Bw_offspring + 1)
response <- cbind(Male_fitness_without_Brownsville$Focal_male_offspring_beta, Male_fitness_without_Brownsville$Bw_offspring_beta)
male_model <- glmmTMB(response ~ Focal_haplotype * Social_haplotype + factor(Duplicate) + (1|Block), data = Male_fitness_without_Brownsville, family = betabinomial(link = "logit"), zi= ~0, na.action = na.fail, REML = FALSE, control = glmmTMBControl(optCtrl = list(iter.max = 1000, eval.max = 1000), profile = TRUE, collect = FALSE))
Table S5: Evaluation of the male adult fitness model. All possible models were evaluated from the global model that included an interaction between focal haplotype and social haplotype, the standalone fixed effect ‘duplicate’, and the random factor ‘Block’. As there was no clear top model, the final model was calculated via model averaging.
if(file.exists("male_dredge.rds")){ # If already done, just load the results
male_dredge <- readRDS("male_dredge.rds")
} else {male_dredge <- dredge(male_model) # If not already done, run the dredge and save the results
lapply(c("male_dredge"), save_it)
}
Male_table <- subset(male_dredge, delta < 6, recalc.weights = FALSE) %>% as.data.frame()
names(Male_table)[names(Male_table) == "df"] <- "Degrees of freedom"
names(Male_table)[names(Male_table) == "logLik"] <- "Log likelihood"
names(Male_table)[names(Male_table) == "AICc"] <- "AICc"
names(Male_table)[names(Male_table) == "delta"] <- "Delta"
names(Male_table)[names(Male_table) == "weight"] <- "Weight"
pander(Male_table, split.cell = 40, split.table = Inf)
| cond((Int)) | disp((Int)) | cond(factor(Duplicate)) | cond(Focal_haplotype) | cond(Social_haplotype) | cond(Focal_haplotype:Social_haplotype) | Degrees of freedom | Log likelihood | AICc | Delta | Weight | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | -0.08234 | + | NA | NA | NA | NA | 3 | -1062 | 2129 | 0 | 0.5731 |
| 2 | -0.114 | + | + | NA | NA | NA | 4 | -1061 | 2131 | 1.715 | 0.2431 |
| 3 | -0.07567 | + | NA | + | NA | NA | 6 | -1060 | 2133 | 3.912 | 0.08105 |
| 5 | 0.04049 | + | NA | NA | + | NA | 7 | -1060 | 2134 | 5.176 | 0.04309 |
| 4 | -0.1043 | + | + | + | NA | NA | 7 | -1060 | 2135 | 5.691 | 0.03329 |
Table 6: Model coefficients, standard error and 95% confidence limits are shown for the male adult fitness averaged model. Bold rows indicate signficant effects.
Male_model_average <-model.avg(male_dredge, subset = delta < 6, fit = TRUE)
Male_CIs <- confint(model.avg(male_dredge, subset = delta < 6)) %>% as.data.frame()
Male_estimate <- coefTable(model.avg(male_dredge, subset = delta < 6)) %>% as.data.frame()
Male_model_avg <- data.frame(Male_estimate, Male_CIs) %>% select(Estimate, Std..Error, X2.5.., X97.5..)
names(Male_model_avg)[names(Male_model_avg) == "Estimate"] <- "Conditional average estimate"
names(Male_model_avg)[names(Male_model_avg) == "Std..Error"] <- "Standard Error"
names(Male_model_avg)[names(Male_model_avg) == "X2.5.."] <- "2.5% Interval"
names(Male_model_avg)[names(Male_model_avg) == "X97.5.."] <- "97.5% Interval"
pander(Male_model_avg, split.cell = 40, split.table = Inf)
| Conditional average estimate | Standard Error | 2.5% Interval | 97.5% Interval | |
|---|---|---|---|---|
| cond((Int)) | -0.08499 | 0.1373 | -0.3541 | 0.1841 |
| cond(factor(Duplicate)2) | 0.1004 | 0.1728 | -0.2381 | 0.439 |
| cond(Focal_haplotypeDahomey) | -0.1583 | 0.2104 | -0.5708 | 0.2541 |
| cond(Focal_haplotypeIsrael) | 0.0001056 | 0.226 | -0.4427 | 0.443 |
| cond(Focal_haplotypeSweden) | 0.1794 | 0.225 | -0.2616 | 0.6204 |
| cond(Social_haplotypeBrownsville) | -0.3478 | 0.2454 | -0.8288 | 0.1333 |
| cond(Social_haplotypeDahomey) | -0.0149 | 0.2565 | -0.5176 | 0.4878 |
| cond(Social_haplotypeIsrael) | -0.1745 | 0.2532 | -0.6707 | 0.3218 |
| cond(Social_haplotypeSweden) | -0.01959 | 0.2582 | -0.5257 | 0.4865 |
# male_cond_plot_data <- Male_fitness %>%
# filter(Focal_male_offspring != 0)
male_cond_summary <- Male_fitness %>%
dplyr::group_by(Social_haplotype) %>%
dplyr::summarise(Social_partner_offspring = sum(Focal_male_offspring), Standard_competitor_offspring = sum(Bw_offspring)) %>%
as.data.frame()
male_cond_summary <- Male_fitness %>%
group_by(Social_haplotype) %>%
dplyr::summarise(Mean_proportion_focal = sum(Proportion_focal) / length(Proportion_focal), Lower = (Mean_proportion_focal - SE(Proportion_focal)* 1.96), Upper = (Mean_proportion_focal + SE(Proportion_focal)*1.96), n = n()) %>% rename(Proportion_focal = Mean_proportion_focal)
Male_cond_plot <- Male_fitness %>%
ggplot(aes(x = Social_haplotype, y = Proportion_focal, fill = Social_haplotype, colour = Social_haplotype)) +
geom_quasirandom(data = Male_fitness, width = 0.3, alpha = 0.5, aes(size = Offspring_counted)) +
scale_size_continuous(range = c(0.5, 6), labels = NULL, breaks = c(20, 40, 60, 80, 100, 120)) +
scale_colour_manual(values = c("Barcelona" = "#a50f15", "Brownsville" = "#fe9929", "Dahomey" = "#41b6c4", "Israel" = "#238443" , "Sweden" = "#4a1486")) +
geom_point(data = male_cond_summary, aes(x = Social_haplotype, y = Proportion_focal), size = 3, colour='black') +
geom_errorbar(data = male_cond_summary, aes(x = Social_haplotype, ymax = Upper, ymin = Lower, width = 0), colour = "black") +
labs(x = "Social mtDNA haplotype", y = "Proportion of offspring sired by focal male") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
Male_cond_plot
Figure 9: Male reproductive success relative to a standard bw competitor is affected by the mtDNA of a social female competitor during larval development. Black points show the mean for each social haplotype and associated confidence intervals. Coloured points show individual males; the size of the point represents the number of offspring produced by both competitors. Data corresponds to the conditional component component of the zero-inflated model.
male_plot_data <- Male_fitness %>%
mutate(Social_survival = replace(as.character(Social_survival), Social_survival == "L", "Died as larva"),
Social_survival = replace(as.character(Social_survival), Social_survival == "P", "Died as pupa"),
Social_survival = replace(as.character(Social_survival), Social_survival == "N", "Survived to adulthood"))
Male_fitness_summary_socialmt <- male_plot_data %>%
group_by(Social_haplotype) %>%
dplyr::summarise(Mean_proportion_focal = sum(Proportion_focal) / length(Proportion_focal), Lower = (Mean_proportion_focal - SE(Proportion_focal)* 1.96), Upper = (Mean_proportion_focal + SE(Proportion_focal)*1.96), n = n()) %>% rename(Proportion_focal = Mean_proportion_focal)
Male_fitness_summary_focalmt <- male_plot_data %>%
group_by(Focal_haplotype) %>%
dplyr::summarise(Mean_proportion_focal = sum(Proportion_focal) / length(Proportion_focal), Lower = (Mean_proportion_focal - SE(Proportion_focal)* 1.96), Upper = (Mean_proportion_focal + SE(Proportion_focal)*1.96), n = n()) %>% rename(Proportion_focal = Mean_proportion_focal)
Male_focal_plot <- male_plot_data %>%
ggplot(aes(x = Focal_haplotype, y = Proportion_focal, fill = Focal_haplotype, colour = Focal_haplotype)) +
geom_quasirandom(data = male_plot_data, width = 0.3, alpha = 0.5, aes(size = Offspring_counted)) +
scale_size_continuous(range = c(0.5, 6), labels = NULL, breaks = c(20, 40, 60, 80, 100, 120)) +
scale_colour_manual(values = c("Barcelona" = "#a50f15", "Brownsville" = "#fe9929", "Dahomey" = "#41b6c4", "Israel" = "#238443" , "Sweden" = "#4a1486")) +
geom_point(data = Male_fitness_summary_focalmt, aes(x = Focal_haplotype, y = Proportion_focal), size = 3, colour='black') +
geom_errorbar(data = Male_fitness_summary_focalmt, aes(x = Focal_haplotype, ymax = Upper, ymin = Lower, width = 0), colour = "black") +
labs(x = "Focal mtDNA haplotype", y = "Proportion of offspring sired by focal male") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
Male_social_plot <- male_plot_data %>%
ggplot(aes(x = Social_haplotype, y = Proportion_focal, fill = Social_haplotype, colour = Social_haplotype)) +
geom_quasirandom(data = male_plot_data, width = 0.3, alpha = 0.5, aes(size = Offspring_counted)) +
scale_size_continuous(range = c(0.5, 6), labels = NULL, breaks = c(20, 40, 60, 80, 100, 120)) +
scale_colour_manual(values = c("Barcelona" = "#a50f15", "Brownsville" = "#fe9929", "Dahomey" = "#41b6c4", "Israel" = "#238443" , "Sweden" = "#4a1486")) +
geom_point(data = Male_fitness_summary_socialmt, aes(x = Social_haplotype, y = Proportion_focal), size = 3, colour='black') +
geom_errorbar(data = Male_fitness_summary_socialmt, aes(x = Social_haplotype, ymax = Upper, ymin = Lower, width = 0), colour = "black") +
labs(x = "Social mtDNA haplotype", y = "Proportion of offspring sired by focal male") +
theme_minimal() +
theme(legend.position = "none") +
theme(panel.grid.major.x = element_blank())
ggarrange(Male_focal_plot, Male_social_plot)
# **Figure 8:** The proportion of offspring produced by focal males competing with standard _bw_ males, split by a) the males mtDNA haplotype and b) the mtDNA haplotype of a social competitor during development. Coloured points represent individual males, with larger points indicating a high number of offspring produced in the vial (sired by either male). Black points show the mean proportion of offspring sired by the focal male, with asssociated 95% confidence intervals. **Means are not adjusted for zero inflation**.
For completeness, transparency and for purposes of data archiving, we include the raw data in this report.
Table S6: the raw dataset used in the present study.
kable(fitness_data %>% filter(!is.na(Survived)), "html") %>%
kable_styling() %>%
scroll_box(width = "100%", height = "800px")
| Individual | Block | Duplicate | Pipette_tip | Sex | Focal_haplotype | Social_haplotype | Survived | Social_survival | Dev_time | Day | Hours | Wing_length | Maternal_female_offspring | Maternal_male_offspring | Maternal_total_offspring | Paternal_focal_offspring | Patneral_bw_offspring | Proportion_focal |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1 | 1 | 1 | F | Barcelona | Barcelona | 1 | L | NA | NA | NA | NA | 35 | 24 | 59 | NA | NA | NA |
| 2 | 1 | 1 | 1 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 3 | 1 | 1 | 2 | F | Brownsville | Barcelona | 1 | N | 249 | 10 | 11 | NA | 36 | 45 | 81 | NA | NA | NA |
| 4 | 1 | 1 | 2 | M | Barcelona | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 41 | 0.0000000 |
| 5 | 1 | 1 | 3 | F | Dahomey | Barcelona | 1 | N | 249 | 10 | 11 | NA | 17 | 23 | 40 | NA | NA | NA |
| 6 | 1 | 1 | 3 | M | Barcelona | Dahomey | 1 | N | 242 | 10 | 4 | NA | NA | NA | NA | 42 | 0 | 1.0000000 |
| 7 | 1 | 1 | 4 | F | Israel | Barcelona | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 8 | 1 | 1 | 4 | M | Barcelona | Israel | 1 | N | 242 | 10 | 4 | NA | NA | NA | NA | 32 | 26 | 0.5517241 |
| 9 | 1 | 1 | 5 | F | Sweden | Barcelona | 1 | N | NA | NA | NA | NA | 7 | 15 | 22 | NA | NA | NA |
| 10 | 1 | 1 | 5 | M | Barcelona | Sweden | 1 | N | 267 | 11 | 5 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 11 | 1 | 1 | 6 | F | Barcelona | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 12 | 1 | 1 | 6 | M | Brownsville | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 15 | 1 | 1 | 8 | F | Dahomey | Brownsville | 1 | N | 242 | 10 | 4 | NA | 23 | 31 | 54 | NA | NA | NA |
| 16 | 1 | 1 | 8 | M | Brownsville | Dahomey | 1 | N | 245 | 10 | 7 | NA | NA | NA | NA | 0 | 63 | 0.0000000 |
| 17 | 1 | 1 | 9 | F | Israel | Brownsville | 1 | N | 243 | 10 | 5 | NA | NA | NA | NA | NA | NA | NA |
| 18 | 1 | 1 | 9 | M | Brownsville | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 19 | 1 | 1 | 10 | F | Sweden | Brownsville | 1 | L | 266 | 11 | 4 | NA | 26 | 39 | 65 | NA | NA | NA |
| 20 | 1 | 1 | 10 | M | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 21 | 1 | 1 | 11 | F | Barcelona | Dahomey | 1 | N | NA | NA | NA | NA | 8 | 21 | 29 | NA | NA | NA |
| 22 | 1 | 1 | 11 | M | Dahomey | Barcelona | 1 | N | 267 | 11 | 5 | NA | NA | NA | NA | 11 | 26 | 0.2972973 |
| 23 | 1 | 1 | 12 | F | Brownsville | Dahomey | 1 | N | 242 | 10 | 4 | NA | 11 | 22 | 33 | NA | NA | NA |
| 24 | 1 | 1 | 12 | M | Dahomey | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 13 | 0.0000000 |
| 25 | 1 | 1 | 13 | F | Dahomey | Dahomey | 1 | N | 265 | 11 | 3 | NA | NA | NA | NA | NA | NA | NA |
| 26 | 1 | 1 | 13 | M | Dahomey | Dahomey | 1 | N | NA | NA | NA | NA | NA | NA | NA | 128 | 0 | 1.0000000 |
| 27 | 1 | 1 | 14 | F | Israel | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 28 | 1 | 1 | 14 | M | Dahomey | Israel | 1 | L | 248 | 10 | 10 | NA | NA | NA | NA | 163 | 0 | 1.0000000 |
| 29 | 1 | 1 | 15 | F | Sweden | Dahomey | 1 | N | 245 | 10 | 7 | NA | 16 | 27 | 43 | NA | NA | NA |
| 30 | 1 | 1 | 15 | M | Dahomey | Sweden | 1 | N | 248 | 10 | 10 | NA | NA | NA | NA | 105 | 0 | 1.0000000 |
| 31 | 1 | 1 | 16 | F | Barcelona | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 32 | 1 | 1 | 16 | M | Israel | Barcelona | 1 | L | 249 | 10 | 11 | NA | NA | NA | NA | 25 | 25 | 0.5000000 |
| 38 | 1 | 1 | 19 | M | Israel | Israel | 1 | NA | 243 | 10 | 5 | NA | NA | NA | NA | 0 | 58 | 0.0000000 |
| 41 | 1 | 1 | 21 | F | Barcelona | Sweden | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 42 | 1 | 1 | 21 | M | Sweden | Barcelona | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 43 | 1 | 1 | 22 | F | Brownsville | Sweden | 1 | N | 270 | 11 | 8 | NA | 31 | 22 | 53 | NA | NA | NA |
| 44 | 1 | 1 | 22 | M | Sweden | Brownsville | 1 | N | 267 | 11 | 5 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 45 | 1 | 1 | 23 | F | Dahomey | Sweden | 1 | N | NA | NA | NA | NA | 23 | 32 | 55 | NA | NA | NA |
| 46 | 1 | 1 | 23 | M | Sweden | Dahomey | 1 | N | 242 | 10 | 4 | NA | NA | NA | NA | 0 | 52 | 0.0000000 |
| 47 | 1 | 1 | 24 | F | Israel | Sweden | 1 | N | NA | NA | NA | NA | 18 | 22 | 40 | NA | NA | NA |
| 48 | 1 | 1 | 24 | M | Sweden | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 91 | 14 | 0.8666667 |
| 49 | 1 | 1 | 25 | F | Sweden | Sweden | 1 | N | 273 | 11 | 11 | NA | 18 | 19 | 37 | NA | NA | NA |
| 50 | 1 | 1 | 25 | M | Sweden | Sweden | 1 | N | NA | NA | NA | NA | NA | NA | NA | 68 | 4 | 0.9444444 |
| 51 | 1 | 1 | 26 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 52 | 1 | 1 | 26 | M | Barcelona | Barcelona | 1 | L | 245 | 10 | 7 | NA | NA | NA | NA | 138 | 0 | 1.0000000 |
| 53 | 1 | 1 | 27 | F | Brownsville | Barcelona | 1 | N | 269 | 11 | 7 | NA | 9 | 17 | 26 | NA | NA | NA |
| 54 | 1 | 1 | 27 | M | Barcelona | Brownsville | 1 | N | 269 | 11 | 7 | NA | NA | NA | NA | 74 | 0 | 1.0000000 |
| 55 | 1 | 1 | 28 | F | Dahomey | Barcelona | 1 | N | 267 | 11 | 5 | NA | 25 | 19 | 44 | NA | NA | NA |
| 56 | 1 | 1 | 28 | M | Barcelona | Dahomey | 1 | N | 283 | 11 | 21 | NA | NA | NA | NA | 0 | 25 | 0.0000000 |
| 57 | 1 | 1 | 29 | F | Israel | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 58 | 1 | 1 | 29 | M | Barcelona | Israel | 1 | P | 288 | 12 | 2 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 59 | 1 | 1 | 30 | F | Sweden | Barcelona | 1 | N | 283 | 11 | 21 | NA | 28 | 19 | 47 | NA | NA | NA |
| 60 | 1 | 1 | 30 | M | Barcelona | Sweden | 1 | N | 283 | 11 | 21 | NA | NA | NA | NA | 70 | 46 | 0.6034483 |
| 61 | 1 | 1 | 31 | F | Barcelona | Brownsville | 1 | N | 269 | 11 | 7 | NA | 0 | 0 | 0 | NA | NA | NA |
| 62 | 1 | 1 | 31 | M | Brownsville | Barcelona | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 32 | 0.0000000 |
| 63 | 1 | 1 | 32 | F | Brownsville | Brownsville | 1 | N | NA | NA | NA | NA | 27 | 22 | 49 | NA | NA | NA |
| 64 | 1 | 1 | 32 | M | Brownsville | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 65 | 1 | 1 | 33 | F | Dahomey | Brownsville | 1 | P | 270 | 11 | 8 | NA | 13 | 16 | 29 | NA | NA | NA |
| 66 | 1 | 1 | 33 | M | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 67 | 1 | 1 | 34 | F | Israel | Brownsville | 1 | N | 273 | 11 | 11 | NA | 0 | 0 | 0 | NA | NA | NA |
| 68 | 1 | 1 | 34 | M | Brownsville | Israel | 1 | N | 270 | 11 | 8 | NA | NA | NA | NA | 0 | 52 | 0.0000000 |
| 69 | 1 | 1 | 35 | F | Sweden | Brownsville | 1 | N | 269 | 11 | 7 | NA | 9 | 10 | 19 | NA | NA | NA |
| 70 | 1 | 1 | 35 | M | Brownsville | Sweden | 1 | N | 271 | 11 | 9 | NA | NA | NA | NA | 0 | 21 | 0.0000000 |
| 71 | 1 | 1 | 36 | F | Barcelona | Dahomey | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 72 | 1 | 1 | 36 | M | Dahomey | Barcelona | 1 | N | 269 | 11 | 7 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 73 | 1 | 1 | 37 | F | Brownsville | Dahomey | 1 | N | 243 | 10 | 5 | NA | 18 | 29 | 47 | NA | NA | NA |
| 74 | 1 | 1 | 37 | M | Dahomey | Brownsville | 1 | N | 248 | 10 | 10 | NA | NA | NA | NA | 0 | 49 | 0.0000000 |
| 75 | 1 | 1 | 38 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 76 | 1 | 1 | 38 | M | Dahomey | Dahomey | 1 | P | 251 | 10 | 13 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 77 | 1 | 1 | 39 | F | Israel | Dahomey | 1 | N | NA | NA | NA | NA | 35 | 20 | 55 | NA | NA | NA |
| 78 | 1 | 1 | 39 | M | Dahomey | Israel | 1 | N | 248 | 10 | 10 | NA | NA | NA | NA | 81 | 8 | 0.9101124 |
| 79 | 1 | 1 | 40 | F | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 80 | 1 | 1 | 40 | M | Dahomey | Sweden | 1 | L | 274 | 11 | 12 | NA | NA | NA | NA | 1 | 23 | 0.0416667 |
| 81 | 1 | 1 | 41 | F | Barcelona | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 82 | 1 | 1 | 41 | M | Israel | Barcelona | 1 | P | 269 | 11 | 7 | NA | NA | NA | NA | 0 | 55 | 0.0000000 |
| 85 | 1 | 1 | 43 | F | Dahomey | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 86 | 1 | 1 | 43 | M | Israel | Dahomey | 1 | P | 267 | 11 | 5 | NA | NA | NA | NA | 200 | 0 | 1.0000000 |
| 87 | 1 | 1 | 44 | F | Israel | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 88 | 1 | 1 | 44 | M | Israel | Israel | 1 | L | 248 | 10 | 10 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 89 | 1 | 1 | 45 | F | Sweden | Israel | 1 | N | 288 | 12 | 2 | NA | 0 | 0 | 0 | NA | NA | NA |
| 90 | 1 | 1 | 45 | M | Israel | Sweden | 1 | N | 270 | 11 | 8 | NA | NA | NA | NA | 22 | 49 | 0.3098592 |
| 91 | 1 | 1 | 46 | F | Barcelona | Sweden | 1 | N | NA | NA | NA | NA | 19 | 34 | 53 | NA | NA | NA |
| 92 | 1 | 1 | 46 | M | Sweden | Barcelona | 1 | N | NA | NA | NA | NA | NA | NA | NA | 75 | 0 | 1.0000000 |
| 93 | 1 | 1 | 47 | F | Brownsville | Sweden | 1 | N | 267 | 11 | 5 | NA | 0 | 0 | 0 | NA | NA | NA |
| 94 | 1 | 1 | 47 | M | Sweden | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 104 | 2 | 0.9811321 |
| 95 | 1 | 1 | 48 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 96 | 1 | 1 | 48 | M | Sweden | Dahomey | 1 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 99 | 1 | 1 | 50 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 100 | 1 | 1 | 50 | M | Sweden | Sweden | 1 | L | NA | NA | NA | NA | NA | NA | NA | 47 | 0 | 1.0000000 |
| 101 | 1 | 1 | 51 | F | Barcelona | Barcelona | 1 | N | 249 | 10 | 11 | NA | 23 | 27 | 50 | NA | NA | NA |
| 102 | 1 | 1 | 51 | M | Barcelona | Barcelona | 1 | N | 249 | 10 | 11 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 103 | 1 | 1 | 52 | F | Brownsville | Barcelona | 1 | N | 269 | 11 | 7 | NA | 0 | 0 | 0 | NA | NA | NA |
| 104 | 1 | 1 | 52 | M | Barcelona | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 141 | 15 | 0.9038462 |
| 105 | 1 | 1 | 53 | F | Dahomey | Barcelona | 1 | N | 246 | 10 | 8 | NA | 22 | 21 | 43 | NA | NA | NA |
| 106 | 1 | 1 | 53 | M | Barcelona | Dahomey | 1 | N | NA | NA | NA | NA | NA | NA | NA | 3 | 27 | 0.1000000 |
| 107 | 1 | 1 | 54 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 108 | 1 | 1 | 54 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 109 | 1 | 1 | 55 | F | Sweden | Barcelona | 1 | N | NA | NA | NA | NA | 8 | 8 | 16 | NA | NA | NA |
| 110 | 1 | 1 | 55 | M | Barcelona | Sweden | 1 | N | NA | NA | NA | NA | NA | NA | NA | 11 | 10 | 0.5238095 |
| 111 | 1 | 1 | 56 | F | Barcelona | Brownsville | 1 | L | NA | NA | NA | NA | 20 | 19 | 39 | NA | NA | NA |
| 112 | 1 | 1 | 56 | M | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 113 | 1 | 1 | 57 | F | Brownsville | Brownsville | 1 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 114 | 1 | 1 | 57 | M | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 117 | 1 | 1 | 59 | F | Israel | Brownsville | 1 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 118 | 1 | 1 | 59 | M | Brownsville | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 119 | 1 | 1 | 60 | F | Sweden | Brownsville | 1 | L | NA | NA | NA | NA | 51 | 50 | 101 | NA | NA | NA |
| 120 | 1 | 1 | 60 | M | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 121 | 1 | 1 | 61 | F | Barcelona | Dahomey | 1 | N | 248 | 10 | 10 | NA | 22 | 18 | 40 | NA | NA | NA |
| 122 | 1 | 1 | 61 | M | Dahomey | Barcelona | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 11 | 0.0000000 |
| 123 | 1 | 1 | 62 | F | Brownsville | Dahomey | 1 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 124 | 1 | 1 | 62 | M | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 125 | 1 | 1 | 63 | F | Dahomey | Dahomey | 1 | N | NA | NA | NA | NA | 23 | 22 | 45 | NA | NA | NA |
| 126 | 1 | 1 | 63 | M | Dahomey | Dahomey | 1 | N | 274 | 11 | 12 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 127 | 1 | 1 | 64 | F | Israel | Dahomey | 1 | N | 274 | 11 | 12 | NA | 0 | 0 | 0 | NA | NA | NA |
| 128 | 1 | 1 | 64 | M | Dahomey | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 48 | 0.0000000 |
| 130 | 1 | 1 | 65 | M | Dahomey | Sweden | 1 | NA | NA | NA | NA | NA | NA | NA | NA | 0 | 95 | 0.0000000 |
| 133 | 1 | 1 | 67 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 134 | 1 | 1 | 67 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 135 | 1 | 1 | 68 | F | Dahomey | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 136 | 1 | 1 | 68 | M | Israel | Dahomey | 1 | L | NA | NA | NA | NA | NA | NA | NA | 94 | 0 | 1.0000000 |
| 137 | 1 | 1 | 69 | F | Israel | Israel | 1 | P | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 138 | 1 | 1 | 69 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 141 | 1 | 1 | 71 | F | Barcelona | Sweden | 1 | N | 287 | 12 | 1 | NA | 0 | 0 | 0 | NA | NA | NA |
| 142 | 1 | 1 | 71 | M | Sweden | Barcelona | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 143 | 1 | 1 | 72 | F | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 144 | 1 | 1 | 72 | M | Sweden | Brownsville | 1 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 147 | 1 | 1 | 74 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 148 | 1 | 1 | 74 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 149 | 1 | 1 | 75 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 150 | 1 | 1 | 75 | M | Sweden | Sweden | 1 | P | NA | NA | NA | NA | NA | NA | NA | 93 | 17 | 0.8454545 |
| 151 | 1 | 2 | 76 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 152 | 1 | 2 | 76 | M | Barcelona | Barcelona | 1 | P | 267 | 11 | 5 | NA | NA | NA | NA | NA | NA | NA |
| 153 | 1 | 2 | 77 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 154 | 1 | 2 | 77 | M | Barcelona | Brownsville | 1 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 117 | 0.0000000 |
| 155 | 1 | 2 | 78 | F | Dahomey | Barcelona | 1 | P | 243 | 10 | 5 | NA | 0 | 0 | 0 | NA | NA | NA |
| 156 | 1 | 2 | 78 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 157 | 1 | 2 | 79 | F | Israel | Barcelona | 1 | N | 269 | 11 | 7 | NA | 5 | 8 | 13 | NA | NA | NA |
| 158 | 1 | 2 | 79 | M | Barcelona | Israel | 1 | N | 269 | 11 | 7 | NA | NA | NA | NA | 0 | 2 | 0.0000000 |
| 159 | 1 | 2 | 80 | F | Sweden | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 160 | 1 | 2 | 80 | M | Barcelona | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 161 | 1 | 2 | 81 | F | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 162 | 1 | 2 | 81 | M | Brownsville | Barcelona | 1 | P | 248 | 10 | 10 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 163 | 1 | 2 | 82 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 164 | 1 | 2 | 82 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 165 | 1 | 2 | 83 | F | Dahomey | Brownsville | 1 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 166 | 1 | 2 | 83 | M | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 167 | 1 | 2 | 84 | F | Israel | Brownsville | 1 | N | 248 | 10 | 10 | NA | 33 | 46 | 79 | NA | NA | NA |
| 168 | 1 | 2 | 84 | M | Brownsville | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 169 | 1 | 2 | 85 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 170 | 1 | 2 | 85 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 171 | 1 | 2 | 86 | F | Barcelona | Dahomey | 1 | N | 248 | 10 | 10 | NA | 28 | 35 | 63 | NA | NA | NA |
| 172 | 1 | 2 | 86 | M | Dahomey | Barcelona | 1 | N | 248 | 10 | 10 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 173 | 1 | 2 | 87 | F | Brownsville | Dahomey | 1 | N | NA | NA | NA | NA | 18 | 19 | 37 | NA | NA | NA |
| 174 | 1 | 2 | 87 | M | Dahomey | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 43 | 0.0000000 |
| 175 | 1 | 2 | 88 | F | Dahomey | Dahomey | 1 | L | NA | NA | NA | NA | 21 | 21 | 42 | NA | NA | NA |
| 176 | 1 | 2 | 88 | M | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 177 | 1 | 2 | 89 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 178 | 1 | 2 | 89 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 179 | 1 | 2 | 90 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 180 | 1 | 2 | 90 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 181 | 1 | 2 | 91 | F | Barcelona | Israel | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 182 | 1 | 2 | 91 | M | Israel | Barcelona | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 28 | 0.0000000 |
| 183 | 1 | 2 | 92 | F | Brownsville | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 184 | 1 | 2 | 92 | M | Israel | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 185 | 1 | 2 | 93 | F | Dahomey | Israel | 1 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 186 | 1 | 2 | 93 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 187 | 1 | 2 | 94 | F | Israel | Israel | 1 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 188 | 1 | 2 | 94 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 189 | 1 | 2 | 95 | F | Sweden | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 190 | 1 | 2 | 95 | M | Israel | Sweden | 1 | L | 250 | 10 | 12 | NA | NA | NA | NA | 64 | 0 | 1.0000000 |
| 191 | 1 | 2 | 96 | F | Barcelona | Sweden | 1 | L | 250 | 10 | 12 | NA | 25 | 30 | 55 | NA | NA | NA |
| 192 | 1 | 2 | 96 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 193 | 1 | 2 | 97 | F | Brownsville | Sweden | 1 | N | NA | NA | NA | NA | 30 | 33 | 63 | NA | NA | NA |
| 194 | 1 | 2 | 97 | M | Sweden | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 97 | 2 | 0.9797980 |
| 195 | 1 | 2 | 98 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 196 | 1 | 2 | 98 | M | Sweden | Dahomey | 1 | P | NA | NA | NA | NA | NA | NA | NA | 116 | 2 | 0.9830508 |
| 197 | 1 | 2 | 99 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 198 | 1 | 2 | 99 | M | Sweden | Israel | 1 | P | 269 | 11 | 7 | NA | NA | NA | NA | 79 | 17 | 0.8229167 |
| 199 | 1 | 2 | 100 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 200 | 1 | 2 | 100 | M | Sweden | Sweden | 1 | L | 248 | 10 | 10 | NA | NA | NA | NA | 96 | 0 | 1.0000000 |
| 201 | 1 | 2 | 101 | F | Barcelona | Barcelona | 1 | P | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 202 | 1 | 2 | 101 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 203 | 1 | 2 | 102 | F | Brownsville | Barcelona | 1 | N | 243 | 10 | 5 | NA | 15 | 18 | 33 | NA | NA | NA |
| 204 | 1 | 2 | 102 | M | Barcelona | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 19 | 51 | 0.2714286 |
| 205 | 1 | 2 | 103 | F | Dahomey | Barcelona | 1 | N | 269 | 11 | 7 | NA | 4 | 6 | 10 | NA | NA | NA |
| 206 | 1 | 2 | 103 | M | Barcelona | Dahomey | 1 | N | NA | NA | NA | NA | NA | NA | NA | 57 | 8 | 0.8769231 |
| 207 | 1 | 2 | 104 | F | Israel | Barcelona | 1 | N | 269 | 11 | 7 | NA | 0 | 0 | 0 | NA | NA | NA |
| 208 | 1 | 2 | 104 | M | Barcelona | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 101 | 0.0000000 |
| 209 | 1 | 2 | 105 | F | Sweden | Barcelona | 1 | N | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 210 | 1 | 2 | 105 | M | Barcelona | Sweden | 1 | N | NA | NA | NA | NA | NA | NA | NA | 79 | 0 | 1.0000000 |
| 213 | 1 | 2 | 107 | F | Brownsville | Brownsville | 1 | N | NA | NA | NA | NA | 17 | 22 | 39 | NA | NA | NA |
| 214 | 1 | 2 | 107 | M | Brownsville | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 215 | 1 | 2 | 108 | F | Dahomey | Brownsville | 1 | N | NA | NA | NA | NA | 28 | 37 | 65 | NA | NA | NA |
| 216 | 1 | 2 | 108 | M | Brownsville | Dahomey | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 34 | 0.0000000 |
| 217 | 1 | 2 | 109 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 218 | 1 | 2 | 109 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 219 | 1 | 2 | 110 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 220 | 1 | 2 | 110 | M | Brownsville | Sweden | 1 | L | 274 | 11 | 12 | NA | NA | NA | NA | 0 | 20 | 0.0000000 |
| 221 | 1 | 2 | 111 | F | Barcelona | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 222 | 1 | 2 | 111 | M | Dahomey | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 223 | 1 | 2 | 112 | F | Brownsville | Dahomey | 1 | N | 267 | 11 | 5 | NA | 0 | 0 | 0 | NA | NA | NA |
| 224 | 1 | 2 | 112 | M | Dahomey | Brownsville | 1 | N | 267 | 11 | 5 | NA | NA | NA | NA | 66 | 0 | 1.0000000 |
| 227 | 1 | 2 | 114 | F | Israel | Dahomey | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 228 | 1 | 2 | 114 | M | Dahomey | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 8 | 0.0000000 |
| 229 | 1 | 2 | 115 | F | Sweden | Dahomey | 1 | N | 267 | 11 | 5 | NA | 0 | 0 | 0 | NA | NA | NA |
| 230 | 1 | 2 | 115 | M | Dahomey | Sweden | 1 | N | 269 | 11 | 7 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 231 | 1 | 2 | 116 | F | Barcelona | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 232 | 1 | 2 | 116 | M | Israel | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 233 | 1 | 2 | 117 | F | Brownsville | Israel | 1 | N | 248 | 10 | 10 | NA | 0 | 0 | 0 | NA | NA | NA |
| 234 | 1 | 2 | 117 | M | Israel | Brownsville | 1 | N | 267 | 11 | 5 | NA | NA | NA | NA | 47 | 0 | 1.0000000 |
| 235 | 1 | 2 | 118 | F | Dahomey | Israel | 1 | N | 270 | 11 | 8 | NA | 30 | 31 | 61 | NA | NA | NA |
| 236 | 1 | 2 | 118 | M | Israel | Dahomey | 1 | N | 274 | 11 | 12 | NA | NA | NA | NA | 11 | 0 | 1.0000000 |
| 237 | 1 | 2 | 119 | F | Israel | Israel | 1 | N | 248 | 10 | 10 | NA | 23 | 47 | 70 | NA | NA | NA |
| 238 | 1 | 2 | 119 | M | Israel | Israel | 1 | N | 248 | 10 | 10 | NA | NA | NA | NA | 19 | 0 | 1.0000000 |
| 239 | 1 | 2 | 120 | F | Sweden | Israel | 1 | P | 248 | 10 | 10 | NA | 37 | 46 | 83 | NA | NA | NA |
| 240 | 1 | 2 | 120 | M | Israel | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 241 | 1 | 2 | 121 | F | Barcelona | Sweden | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 242 | 1 | 2 | 121 | M | Sweden | Barcelona | 1 | N | 269 | 11 | 7 | NA | NA | NA | NA | 21 | 19 | 0.5250000 |
| 243 | 1 | 2 | 122 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 244 | 1 | 2 | 122 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 247 | 1 | 2 | 124 | F | Israel | Sweden | 1 | N | 250 | 10 | 12 | NA | 26 | 17 | 43 | NA | NA | NA |
| 248 | 1 | 2 | 124 | M | Sweden | Israel | 1 | N | 267 | 11 | 5 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 249 | 1 | 2 | 125 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 250 | 1 | 2 | 125 | M | Sweden | Sweden | 1 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 1 | 0.0000000 |
| 251 | 1 | 2 | 126 | F | Barcelona | Barcelona | 1 | N | 274 | 11 | 12 | NA | 16 | 20 | 36 | NA | NA | NA |
| 252 | 1 | 2 | 126 | M | Barcelona | Barcelona | 1 | N | 288 | 12 | 2 | NA | NA | NA | NA | 0 | 74 | 0.0000000 |
| 253 | 1 | 2 | 127 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 254 | 1 | 2 | 127 | M | Barcelona | Brownsville | 1 | L | 269 | 11 | 7 | NA | NA | NA | NA | 29 | 0 | 1.0000000 |
| 255 | 1 | 2 | 128 | F | Dahomey | Barcelona | 1 | L | 247 | 10 | 9 | NA | 40 | 43 | 83 | NA | NA | NA |
| 256 | 1 | 2 | 128 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 257 | 1 | 2 | 129 | F | Israel | Barcelona | 1 | L | NA | NA | NA | NA | 35 | 33 | 68 | NA | NA | NA |
| 258 | 1 | 2 | 129 | M | Barcelona | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 259 | 1 | 2 | 130 | F | Sweden | Barcelona | 1 | P | NA | NA | NA | NA | 50 | 27 | 77 | NA | NA | NA |
| 260 | 1 | 2 | 130 | M | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 261 | 1 | 2 | 131 | F | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 262 | 1 | 2 | 131 | M | Brownsville | Barcelona | 1 | P | 267 | 11 | 5 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 263 | 1 | 2 | 132 | F | Brownsville | Brownsville | 1 | L | NA | NA | NA | NA | 38 | 46 | 84 | NA | NA | NA |
| 264 | 1 | 2 | 132 | M | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 265 | 1 | 2 | 133 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 266 | 1 | 2 | 133 | M | Brownsville | Dahomey | 1 | P | 269 | 11 | 7 | NA | NA | NA | NA | NA | NA | NA |
| 267 | 1 | 2 | 134 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 268 | 1 | 2 | 134 | M | Brownsville | Israel | 1 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 33 | 0.0000000 |
| 269 | 1 | 2 | 135 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 270 | 1 | 2 | 135 | M | Brownsville | Sweden | 1 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 271 | 1 | 2 | 136 | F | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 272 | 1 | 2 | 136 | M | Dahomey | Barcelona | 1 | L | 267 | 11 | 5 | NA | NA | NA | NA | 89 | 0 | 1.0000000 |
| 273 | 1 | 2 | 137 | F | Brownsville | Dahomey | 1 | L | 243 | 10 | 5 | NA | NA | NA | NA | NA | NA | NA |
| 274 | 1 | 2 | 137 | M | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 275 | 1 | 2 | 138 | F | Dahomey | Dahomey | 1 | N | NA | NA | NA | NA | 14 | 13 | 27 | NA | NA | NA |
| 276 | 1 | 2 | 138 | M | Dahomey | Dahomey | 1 | N | 270 | 11 | 8 | NA | NA | NA | NA | 124 | 0 | 1.0000000 |
| 277 | 1 | 2 | 139 | F | Israel | Dahomey | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 278 | 1 | 2 | 139 | M | Dahomey | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 281 | 1 | 2 | 141 | F | Barcelona | Israel | 1 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 282 | 1 | 2 | 141 | M | Israel | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 283 | 1 | 2 | 142 | F | Brownsville | Israel | 1 | L | 250 | 10 | 12 | NA | 0 | 0 | 0 | NA | NA | NA |
| 284 | 1 | 2 | 142 | M | Israel | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 285 | 1 | 2 | 143 | F | Dahomey | Israel | 1 | P | 293 | 12 | 7 | NA | 0 | 0 | 0 | NA | NA | NA |
| 286 | 1 | 2 | 143 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 287 | 1 | 2 | 144 | F | Israel | Israel | 1 | L | 250 | 10 | 12 | NA | 0 | 0 | 0 | NA | NA | NA |
| 288 | 1 | 2 | 144 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 291 | 1 | 2 | 146 | F | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 292 | 1 | 2 | 146 | M | Sweden | Barcelona | 1 | L | 269 | 11 | 7 | NA | NA | NA | NA | 18 | 0 | 1.0000000 |
| 293 | 1 | 2 | 147 | F | Brownsville | Sweden | 1 | N | 267 | 11 | 5 | NA | 24 | 23 | 47 | NA | NA | NA |
| 294 | 1 | 2 | 147 | M | Sweden | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 64 | 9 | 0.8767123 |
| 295 | 1 | 2 | 148 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 296 | 1 | 2 | 148 | M | Sweden | Dahomey | 1 | L | 267 | 11 | 5 | NA | NA | NA | NA | 69 | 11 | 0.8625000 |
| 297 | 1 | 2 | 149 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 298 | 1 | 2 | 149 | M | Sweden | Israel | 1 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 45 | 0.0000000 |
| 299 | 1 | 2 | 150 | F | Sweden | Sweden | 1 | P | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 300 | 1 | 2 | 150 | M | Sweden | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 301 | 2 | 1 | 151 | F | Barcelona | Barcelona | 1 | N | 287 | 12 | 1 | NA | 0 | 0 | 0 | NA | NA | NA |
| 302 | 2 | 1 | 151 | M | Barcelona | Barcelona | 1 | N | 289 | 12 | 3 | NA | NA | NA | NA | 110 | 7 | 0.9401709 |
| 303 | 2 | 1 | 152 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 304 | 2 | 1 | 152 | M | Barcelona | Brownsville | 1 | L | 294 | 12 | 8 | NA | NA | NA | NA | 94 | 0 | 1.0000000 |
| 305 | 2 | 1 | 153 | F | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 306 | 2 | 1 | 153 | M | Barcelona | Dahomey | 1 | L | 287 | 12 | 1 | NA | NA | NA | NA | 14 | 0 | 1.0000000 |
| 307 | 2 | 1 | 154 | F | Israel | Barcelona | 1 | P | 272 | 11 | 10 | NA | NA | NA | NA | NA | NA | NA |
| 308 | 2 | 1 | 154 | M | Barcelona | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 309 | 2 | 1 | 155 | F | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 310 | 2 | 1 | 155 | M | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 311 | 2 | 1 | 156 | F | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 312 | 2 | 1 | 156 | M | Brownsville | Barcelona | 1 | P | 290 | 12 | 4 | NA | NA | NA | NA | 0 | 88 | 0.0000000 |
| 313 | 2 | 1 | 157 | F | Brownsville | Brownsville | 1 | N | 269 | 11 | 7 | NA | 36 | 37 | 73 | NA | NA | NA |
| 314 | 2 | 1 | 157 | M | Brownsville | Brownsville | 1 | N | 268 | 11 | 6 | NA | NA | NA | NA | 0 | 21 | 0.0000000 |
| 315 | 2 | 1 | 158 | F | Dahomey | Brownsville | 1 | N | 288 | 12 | 2 | NA | 19 | 32 | 51 | NA | NA | NA |
| 316 | 2 | 1 | 158 | M | Brownsville | Dahomey | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 88 | 0.0000000 |
| 317 | 2 | 1 | 159 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 318 | 2 | 1 | 159 | M | Brownsville | Israel | 1 | L | 286 | 12 | 0 | NA | NA | NA | NA | 18 | 75 | 0.1935484 |
| 319 | 2 | 1 | 160 | F | Sweden | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 320 | 2 | 1 | 160 | M | Brownsville | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 321 | 2 | 1 | 161 | F | Barcelona | Dahomey | 1 | N | 296 | 12 | 10 | NA | 0 | 0 | 0 | NA | NA | NA |
| 322 | 2 | 1 | 161 | M | Dahomey | Barcelona | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 72 | 0.0000000 |
| 323 | 2 | 1 | 162 | F | Brownsville | Dahomey | 1 | N | 298 | 12 | 12 | NA | 19 | 16 | 35 | NA | NA | NA |
| 324 | 2 | 1 | 162 | M | Dahomey | Brownsville | 1 | N | 295 | 12 | 9 | NA | NA | NA | NA | 46 | 23 | 0.6666667 |
| 325 | 2 | 1 | 163 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 326 | 2 | 1 | 163 | M | Dahomey | Dahomey | 1 | P | 286 | 12 | 0 | NA | NA | NA | NA | 0 | 26 | 0.0000000 |
| 327 | 2 | 1 | 164 | F | Israel | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 328 | 2 | 1 | 164 | M | Dahomey | Israel | 1 | L | 266 | 11 | 4 | NA | NA | NA | NA | 0 | 29 | 0.0000000 |
| 329 | 2 | 1 | 165 | F | Sweden | Dahomey | 1 | N | 269 | 11 | 7 | NA | 39 | 24 | 63 | NA | NA | NA |
| 330 | 2 | 1 | 165 | M | Dahomey | Sweden | 1 | N | 275 | 11 | 13 | NA | NA | NA | NA | 33 | 16 | 0.6734694 |
| 331 | 2 | 1 | 166 | F | Barcelona | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 332 | 2 | 1 | 166 | M | Israel | Barcelona | 1 | P | 267 | 11 | 5 | NA | NA | NA | NA | 0 | 6 | 0.0000000 |
| 333 | 2 | 1 | 167 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 334 | 2 | 1 | 167 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 335 | 2 | 1 | 168 | F | Dahomey | Israel | 1 | L | 287 | 12 | 1 | NA | 39 | 28 | 67 | NA | NA | NA |
| 336 | 2 | 1 | 168 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 337 | 2 | 1 | 169 | F | Israel | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 338 | 2 | 1 | 169 | M | Israel | Israel | 1 | L | 275 | 11 | 13 | NA | NA | NA | NA | 34 | 10 | 0.7727273 |
| 339 | 2 | 1 | 170 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 340 | 2 | 1 | 170 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 341 | 2 | 1 | 171 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 342 | 2 | 1 | 171 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 343 | 2 | 1 | 172 | F | Brownsville | Sweden | 1 | L | 264 | 11 | 2 | NA | 26 | 32 | 58 | NA | NA | NA |
| 344 | 2 | 1 | 172 | M | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 345 | 2 | 1 | 173 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 346 | 2 | 1 | 173 | M | Sweden | Dahomey | 1 | P | NA | NA | NA | NA | NA | NA | NA | 45 | 1 | 0.9782609 |
| 347 | 2 | 1 | 174 | F | Israel | Sweden | 1 | L | 289 | 12 | 3 | NA | 47 | 41 | 88 | NA | NA | NA |
| 348 | 2 | 1 | 174 | M | Sweden | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 349 | 2 | 1 | 175 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 350 | 2 | 1 | 175 | M | Sweden | Sweden | 1 | P | 269 | 11 | 7 | NA | NA | NA | NA | 12 | 0 | 1.0000000 |
| 351 | 2 | 1 | 176 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 352 | 2 | 1 | 176 | M | Barcelona | Barcelona | 1 | P | 286 | 12 | 0 | NA | NA | NA | NA | 23 | 37 | 0.3833333 |
| 353 | 2 | 1 | 177 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 354 | 2 | 1 | 177 | M | Barcelona | Brownsville | 1 | P | 268 | 11 | 6 | NA | NA | NA | NA | 107 | 13 | 0.8916667 |
| 355 | 2 | 1 | 178 | F | Dahomey | Barcelona | 1 | N | 264 | 11 | 2 | NA | 28 | 20 | 48 | NA | NA | NA |
| 356 | 2 | 1 | 178 | M | Barcelona | Dahomey | 1 | N | 271 | 11 | 9 | NA | NA | NA | NA | 48 | 0 | 1.0000000 |
| 357 | 2 | 1 | 179 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 358 | 2 | 1 | 179 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 359 | 2 | 1 | 180 | F | Sweden | Barcelona | 1 | L | 248 | 10 | 10 | NA | 36 | 37 | 73 | NA | NA | NA |
| 360 | 2 | 1 | 180 | M | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 361 | 2 | 1 | 181 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 362 | 2 | 1 | 181 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 363 | 2 | 1 | 182 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 364 | 2 | 1 | 182 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 365 | 2 | 1 | 183 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 366 | 2 | 1 | 183 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 367 | 2 | 1 | 184 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 368 | 2 | 1 | 184 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 369 | 2 | 1 | 185 | F | Sweden | Brownsville | 1 | N | 268 | 11 | 6 | NA | 2 | 6 | 8 | NA | NA | NA |
| 370 | 2 | 1 | 185 | M | Brownsville | Sweden | 1 | N | 250 | 10 | 12 | NA | NA | NA | NA | 0 | 69 | 0.0000000 |
| 371 | 2 | 1 | 186 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 372 | 2 | 1 | 186 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 373 | 2 | 1 | 187 | F | Brownsville | Dahomey | 1 | N | 271 | 11 | 9 | NA | 26 | 37 | 63 | NA | NA | NA |
| 374 | 2 | 1 | 187 | M | Dahomey | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 375 | 2 | 1 | 188 | F | Dahomey | Dahomey | 1 | P | 245 | 10 | 7 | NA | 9 | 10 | 19 | NA | NA | NA |
| 376 | 2 | 1 | 188 | M | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 377 | 2 | 1 | 189 | F | Israel | Dahomey | 1 | N | NA | NA | NA | NA | 17 | 22 | 39 | NA | NA | NA |
| 378 | 2 | 1 | 189 | M | Dahomey | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 379 | 2 | 1 | 190 | F | Sweden | Dahomey | 1 | N | 286 | 12 | 0 | NA | 24 | 26 | 50 | NA | NA | NA |
| 380 | 2 | 1 | 190 | M | Dahomey | Sweden | 1 | N | 270 | 11 | 8 | NA | NA | NA | NA | 64 | 28 | 0.6956522 |
| 381 | 2 | 1 | 191 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 382 | 2 | 1 | 191 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 383 | 2 | 1 | 192 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 384 | 2 | 1 | 192 | M | Israel | Brownsville | 1 | P | 273 | 11 | 11 | NA | NA | NA | NA | 64 | 0 | 1.0000000 |
| 385 | 2 | 1 | 193 | F | Dahomey | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 386 | 2 | 1 | 193 | M | Israel | Dahomey | 1 | N | 286 | 12 | 0 | NA | NA | NA | NA | 0 | 49 | 0.0000000 |
| 387 | 2 | 1 | 194 | F | Israel | Israel | 1 | N | 269 | 11 | 7 | NA | 0 | 0 | 0 | NA | NA | NA |
| 388 | 2 | 1 | 194 | M | Israel | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 389 | 2 | 1 | 195 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 390 | 2 | 1 | 195 | M | Israel | Sweden | 1 | P | 264 | 11 | 2 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 391 | 2 | 1 | 196 | F | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 392 | 2 | 1 | 196 | M | Sweden | Barcelona | 1 | N | 266 | 11 | 4 | NA | NA | NA | NA | 23 | 5 | 0.8214286 |
| 393 | 2 | 1 | 197 | F | Brownsville | Sweden | 1 | N | 271 | 11 | 9 | NA | 0 | 0 | 0 | NA | NA | NA |
| 394 | 2 | 1 | 197 | M | Sweden | Brownsville | 1 | L | 264 | 11 | 2 | NA | NA | NA | NA | 19 | 0 | 1.0000000 |
| 395 | 2 | 1 | 198 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 396 | 2 | 1 | 198 | M | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 397 | 2 | 1 | 199 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 398 | 2 | 1 | 199 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 399 | 2 | 1 | 200 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 400 | 2 | 1 | 200 | M | Sweden | Sweden | 1 | P | 266 | 11 | 4 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 401 | 2 | 1 | 201 | F | Barcelona | Barcelona | 1 | N | 268 | 11 | 6 | NA | 0 | 0 | 0 | NA | NA | NA |
| 402 | 2 | 1 | 201 | M | Barcelona | Barcelona | 1 | N | 266 | 11 | 4 | NA | NA | NA | NA | 59 | 66 | 0.4720000 |
| 403 | 2 | 1 | 202 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 404 | 2 | 1 | 202 | M | Barcelona | Brownsville | 1 | L | 272 | 11 | 10 | NA | NA | NA | NA | 17 | 0 | 1.0000000 |
| 405 | 2 | 1 | 203 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 406 | 2 | 1 | 203 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 407 | 2 | 1 | 204 | F | Israel | Barcelona | 1 | N | NA | NA | NA | NA | 29 | 17 | 46 | NA | NA | NA |
| 408 | 2 | 1 | 204 | M | Barcelona | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 96 | 0 | 1.0000000 |
| 409 | 2 | 1 | 205 | F | Sweden | Barcelona | 1 | N | 287 | 12 | 1 | NA | 18 | 25 | 43 | NA | NA | NA |
| 410 | 2 | 1 | 205 | M | Barcelona | Sweden | 1 | N | 275 | 11 | 13 | NA | NA | NA | NA | 0 | 50 | 0.0000000 |
| 411 | 2 | 1 | 206 | F | Barcelona | Brownsville | 1 | L | 269 | 11 | 7 | NA | 26 | 26 | 52 | NA | NA | NA |
| 412 | 2 | 1 | 206 | M | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 413 | 2 | 1 | 207 | F | Brownsville | Brownsville | 1 | N | NA | NA | NA | NA | 26 | 38 | 64 | NA | NA | NA |
| 414 | 2 | 1 | 207 | M | Brownsville | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 100 | 0.0000000 |
| 415 | 2 | 1 | 208 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 416 | 2 | 1 | 208 | M | Brownsville | Dahomey | 1 | L | 270 | 11 | 8 | NA | NA | NA | NA | 0 | 49 | 0.0000000 |
| 417 | 2 | 1 | 209 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 418 | 2 | 1 | 209 | M | Brownsville | Israel | 1 | L | 263 | 10 | 1 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 419 | 2 | 1 | 210 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 420 | 2 | 1 | 210 | M | Brownsville | Sweden | 1 | L | 264 | 11 | 2 | NA | NA | NA | NA | 0 | 90 | 0.0000000 |
| 421 | 2 | 1 | 211 | F | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 422 | 2 | 1 | 211 | M | Dahomey | Barcelona | 1 | L | 283 | 11 | 21 | NA | NA | NA | NA | 57 | 7 | 0.8906250 |
| 423 | 2 | 1 | 212 | F | Brownsville | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 424 | 2 | 1 | 212 | M | Dahomey | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 425 | 2 | 1 | 213 | F | Dahomey | Dahomey | 1 | N | 266 | 11 | 4 | NA | 26 | 30 | 56 | NA | NA | NA |
| 426 | 2 | 1 | 213 | M | Dahomey | Dahomey | 1 | N | 266 | 11 | 4 | NA | NA | NA | NA | 23 | 2 | 0.9200000 |
| 427 | 2 | 1 | 214 | F | Israel | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 428 | 2 | 1 | 214 | M | Dahomey | Israel | 1 | L | 249 | 10 | 11 | NA | NA | NA | NA | 13 | 68 | 0.1604938 |
| 429 | 2 | 1 | 215 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 430 | 2 | 1 | 215 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 431 | 2 | 1 | 216 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 432 | 2 | 1 | 216 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 433 | 2 | 1 | 217 | F | Brownsville | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 434 | 2 | 1 | 217 | M | Israel | Brownsville | 1 | L | 291 | 12 | 5 | NA | NA | NA | NA | 0 | 55 | 0.0000000 |
| 435 | 2 | 1 | 218 | F | Dahomey | Israel | 1 | L | NA | NA | NA | NA | 26 | 13 | 39 | NA | NA | NA |
| 436 | 2 | 1 | 218 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 439 | 2 | 1 | 220 | F | Sweden | Israel | 1 | L | 297 | 12 | 11 | NA | 17 | 22 | 39 | NA | NA | NA |
| 440 | 2 | 1 | 220 | M | Israel | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 441 | 2 | 1 | 221 | F | Barcelona | Sweden | 1 | N | 269 | 11 | 7 | NA | 31 | 19 | 50 | NA | NA | NA |
| 442 | 2 | 1 | 221 | M | Sweden | Barcelona | 1 | N | 294 | 12 | 8 | NA | NA | NA | NA | 0 | 27 | 0.0000000 |
| 443 | 2 | 1 | 222 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 444 | 2 | 1 | 222 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 445 | 2 | 1 | 223 | F | Dahomey | Sweden | 1 | N | 262 | 10 | 0 | NA | 35 | 30 | 65 | NA | NA | NA |
| 446 | 2 | 1 | 223 | M | Sweden | Dahomey | 1 | N | 266 | 11 | 4 | NA | NA | NA | NA | 0 | 34 | 0.0000000 |
| 447 | 2 | 1 | 224 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 448 | 2 | 1 | 224 | M | Sweden | Israel | 1 | L | 265 | 11 | 3 | NA | NA | NA | NA | 79 | 7 | 0.9186047 |
| 449 | 2 | 1 | 225 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 450 | 2 | 1 | 225 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 451 | 2 | 1 | 226 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 452 | 2 | 1 | 226 | M | Barcelona | Barcelona | 1 | P | 270 | 11 | 8 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 453 | 2 | 1 | 227 | F | Brownsville | Barcelona | 1 | L | 266 | 11 | 4 | NA | 45 | 56 | 101 | NA | NA | NA |
| 454 | 2 | 1 | 227 | M | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 455 | 2 | 1 | 228 | F | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 456 | 2 | 1 | 228 | M | Barcelona | Dahomey | 1 | P | 277 | 11 | 15 | NA | NA | NA | NA | 59 | 0 | 1.0000000 |
| 457 | 2 | 1 | 229 | F | Israel | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 458 | 2 | 1 | 229 | M | Barcelona | Israel | 1 | P | 271 | 11 | 9 | NA | NA | NA | NA | 74 | 0 | 1.0000000 |
| 461 | 2 | 1 | 231 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 462 | 2 | 1 | 231 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 463 | 2 | 1 | 232 | F | Brownsville | Brownsville | 1 | N | 265 | 11 | 3 | NA | 0 | 0 | 0 | NA | NA | NA |
| 464 | 2 | 1 | 232 | M | Brownsville | Brownsville | 1 | N | 265 | 11 | 3 | NA | NA | NA | NA | 0 | 37 | 0.0000000 |
| 465 | 2 | 1 | 233 | F | Dahomey | Brownsville | 1 | N | 286 | 12 | 0 | NA | 17 | 31 | 48 | NA | NA | NA |
| 466 | 2 | 1 | 233 | M | Brownsville | Dahomey | 1 | N | 264 | 11 | 2 | NA | NA | NA | NA | 0 | 66 | 0.0000000 |
| 467 | 2 | 1 | 234 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 468 | 2 | 1 | 234 | M | Brownsville | Israel | 1 | P | 276 | 11 | 14 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 469 | 2 | 1 | 235 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 470 | 2 | 1 | 235 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 471 | 2 | 1 | 236 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 472 | 2 | 1 | 236 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 473 | 2 | 1 | 237 | F | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 474 | 2 | 1 | 237 | M | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 475 | 2 | 1 | 238 | F | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 476 | 2 | 1 | 238 | M | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 479 | 2 | 1 | 240 | F | Sweden | Dahomey | 1 | L | 272 | 11 | 10 | NA | 34 | 40 | 74 | NA | NA | NA |
| 480 | 2 | 1 | 240 | M | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 481 | 2 | 1 | 241 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 482 | 2 | 1 | 241 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 483 | 2 | 1 | 242 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 484 | 2 | 1 | 242 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 491 | 2 | 1 | 246 | F | Barcelona | Sweden | 1 | P | 287 | 12 | 1 | NA | 22 | 25 | 47 | NA | NA | NA |
| 492 | 2 | 1 | 246 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 493 | 2 | 1 | 247 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 494 | 2 | 1 | 247 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 495 | 2 | 1 | 248 | F | Dahomey | Sweden | 1 | L | 270 | 11 | 8 | NA | 38 | 33 | 71 | NA | NA | NA |
| 496 | 2 | 1 | 248 | M | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 497 | 2 | 1 | 249 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 498 | 2 | 1 | 249 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 499 | 2 | 1 | 250 | F | Sweden | Sweden | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 500 | 2 | 1 | 250 | M | Sweden | Sweden | 1 | N | 294 | 12 | 8 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 501 | 2 | 2 | 251 | F | Barcelona | Barcelona | 1 | N | 246 | 10 | 8 | NA | 25 | 20 | 45 | NA | NA | NA |
| 502 | 2 | 2 | 251 | M | Barcelona | Barcelona | 1 | N | 271 | 11 | 9 | NA | NA | NA | NA | 0 | 64 | 0.0000000 |
| 503 | 2 | 2 | 252 | F | Brownsville | Barcelona | 1 | N | 271 | 11 | 9 | NA | 0 | 0 | 0 | NA | NA | NA |
| 504 | 2 | 2 | 252 | M | Barcelona | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 507 | 2 | 2 | 254 | F | Israel | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 508 | 2 | 2 | 254 | M | Barcelona | Israel | 1 | P | 262 | 10 | 0 | NA | NA | NA | NA | 0 | 80 | 0.0000000 |
| 511 | 2 | 2 | 256 | F | Barcelona | Brownsville | 1 | N | NA | NA | NA | NA | 32 | 25 | 57 | NA | NA | NA |
| 512 | 2 | 2 | 256 | M | Brownsville | Barcelona | 1 | N | 270 | 11 | 8 | NA | NA | NA | NA | 0 | 62 | 0.0000000 |
| 513 | 2 | 2 | 257 | F | Brownsville | Brownsville | 1 | N | 261 | 10 | 23 | NA | 31 | 33 | 64 | NA | NA | NA |
| 514 | 2 | 2 | 257 | M | Brownsville | Brownsville | 1 | N | 294 | 12 | 8 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 515 | 2 | 2 | 258 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 516 | 2 | 2 | 258 | M | Brownsville | Dahomey | 1 | L | 264 | 11 | 2 | NA | NA | NA | NA | 0 | 18 | 0.0000000 |
| 517 | 2 | 2 | 259 | F | Israel | Brownsville | 1 | N | 249 | 10 | 11 | NA | 0 | 0 | 0 | NA | NA | NA |
| 518 | 2 | 2 | 259 | M | Brownsville | Israel | 1 | N | 271 | 11 | 9 | NA | NA | NA | NA | 67 | 16 | 0.8072289 |
| 519 | 2 | 2 | 260 | F | Sweden | Brownsville | 1 | N | 306 | 12 | 20 | NA | 0 | 0 | 0 | NA | NA | NA |
| 520 | 2 | 2 | 260 | M | Brownsville | Sweden | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 521 | 2 | 2 | 261 | F | Barcelona | Dahomey | 1 | N | 246 | 10 | 8 | NA | 35 | 39 | 74 | NA | NA | NA |
| 522 | 2 | 2 | 261 | M | Dahomey | Barcelona | 1 | N | 268 | 11 | 6 | NA | NA | NA | NA | 32 | 0 | 1.0000000 |
| 523 | 2 | 2 | 262 | F | Brownsville | Dahomey | 1 | N | 268 | 11 | 6 | NA | 27 | 31 | 58 | NA | NA | NA |
| 524 | 2 | 2 | 262 | M | Dahomey | Brownsville | 1 | N | 263 | 10 | 1 | NA | NA | NA | NA | 58 | 29 | 0.6666667 |
| 525 | 2 | 2 | 263 | F | Dahomey | Dahomey | 1 | L | 246 | 10 | 8 | NA | 0 | 0 | 0 | NA | NA | NA |
| 526 | 2 | 2 | 263 | M | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 527 | 2 | 2 | 264 | F | Israel | Dahomey | 1 | N | 294 | 12 | 8 | NA | 0 | 0 | 0 | NA | NA | NA |
| 528 | 2 | 2 | 264 | M | Dahomey | Israel | 1 | N | 302 | 12 | 16 | NA | NA | NA | NA | 12 | 82 | 0.1276596 |
| 529 | 2 | 2 | 265 | F | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 530 | 2 | 2 | 265 | M | Dahomey | Sweden | 1 | L | 249 | 10 | 11 | NA | NA | NA | NA | 81 | 0 | 1.0000000 |
| 531 | 2 | 2 | 266 | F | Barcelona | Israel | 1 | N | 249 | 10 | 11 | NA | 57 | 72 | 129 | NA | NA | NA |
| 532 | 2 | 2 | 266 | M | Israel | Barcelona | 1 | N | 267 | 11 | 5 | NA | NA | NA | NA | 26 | 63 | 0.2921348 |
| 533 | 2 | 2 | 267 | F | Brownsville | Israel | 1 | P | 298 | 12 | 12 | NA | 0 | 0 | 0 | NA | NA | NA |
| 534 | 2 | 2 | 267 | M | Israel | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 535 | 2 | 2 | 268 | F | Dahomey | Israel | 1 | L | 250 | 10 | 12 | NA | 27 | 33 | 60 | NA | NA | NA |
| 536 | 2 | 2 | 268 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 537 | 2 | 2 | 269 | F | Israel | Israel | 1 | N | 244 | 10 | 6 | NA | 33 | 40 | 73 | NA | NA | NA |
| 538 | 2 | 2 | 269 | M | Israel | Israel | 1 | N | 312 | 13 | 2 | NA | NA | NA | NA | 57 | 34 | 0.6263736 |
| 539 | 2 | 2 | 270 | F | Sweden | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 540 | 2 | 2 | 270 | M | Israel | Sweden | 1 | P | 248 | 10 | 10 | NA | NA | NA | NA | 54 | 26 | 0.6750000 |
| 541 | 2 | 2 | 271 | F | Barcelona | Sweden | 1 | P | 267 | 11 | 5 | NA | 18 | 20 | 38 | NA | NA | NA |
| 542 | 2 | 2 | 271 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 543 | 2 | 2 | 272 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 544 | 2 | 2 | 272 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 545 | 2 | 2 | 273 | F | Dahomey | Sweden | 1 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 546 | 2 | 2 | 273 | M | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 547 | 2 | 2 | 274 | F | Israel | Sweden | 1 | N | NA | NA | NA | NA | 30 | 24 | 54 | NA | NA | NA |
| 548 | 2 | 2 | 274 | M | Sweden | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 46 | 0.0000000 |
| 549 | 2 | 2 | 275 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 550 | 2 | 2 | 275 | M | Sweden | Sweden | 1 | L | 267 | 11 | 5 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 551 | 2 | 2 | 276 | F | Barcelona | Barcelona | 1 | L | 275 | 11 | 13 | NA | 16 | 19 | 35 | NA | NA | NA |
| 552 | 2 | 2 | 276 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 553 | 2 | 2 | 277 | F | Brownsville | Barcelona | 1 | N | 294 | 12 | 8 | NA | 11 | 13 | 24 | NA | NA | NA |
| 554 | 2 | 2 | 277 | M | Barcelona | Brownsville | 1 | N | 267 | 11 | 5 | NA | NA | NA | NA | 0 | 29 | 0.0000000 |
| 555 | 2 | 2 | 278 | F | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 556 | 2 | 2 | 278 | M | Barcelona | Dahomey | 1 | L | 265 | 11 | 3 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 557 | 2 | 2 | 279 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 558 | 2 | 2 | 279 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 559 | 2 | 2 | 280 | F | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 560 | 2 | 2 | 280 | M | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 561 | 2 | 2 | 281 | F | Barcelona | Brownsville | 1 | N | NA | NA | NA | NA | 29 | 28 | 57 | NA | NA | NA |
| 562 | 2 | 2 | 281 | M | Brownsville | Barcelona | 1 | N | 270 | 11 | 8 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 563 | 2 | 2 | 282 | F | Brownsville | Brownsville | 1 | N | 246 | 10 | 8 | NA | 0 | 0 | 0 | NA | NA | NA |
| 564 | 2 | 2 | 282 | M | Brownsville | Brownsville | 1 | N | 266 | 11 | 4 | NA | NA | NA | NA | 0 | 53 | 0.0000000 |
| 567 | 2 | 2 | 284 | F | Israel | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 568 | 2 | 2 | 284 | M | Brownsville | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 569 | 2 | 2 | 285 | F | Sweden | Brownsville | 1 | N | 245 | 10 | 7 | NA | 0 | 0 | 0 | NA | NA | NA |
| 570 | 2 | 2 | 285 | M | Brownsville | Sweden | 1 | N | 288 | 12 | 2 | NA | NA | NA | NA | 0 | 58 | 0.0000000 |
| 571 | 2 | 2 | 286 | F | Barcelona | Dahomey | 1 | N | 264 | 11 | 2 | NA | 21 | 23 | 44 | NA | NA | NA |
| 572 | 2 | 2 | 286 | M | Dahomey | Barcelona | 1 | N | 294 | 12 | 8 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 581 | 2 | 2 | 291 | F | Barcelona | Israel | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 582 | 2 | 2 | 291 | M | Israel | Barcelona | 1 | N | NA | NA | NA | NA | NA | NA | NA | 51 | 41 | 0.5543478 |
| 583 | 2 | 2 | 292 | F | Brownsville | Israel | 1 | N | NA | NA | NA | NA | 7 | 4 | 11 | NA | NA | NA |
| 584 | 2 | 2 | 292 | M | Israel | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | 45 | 1 | 0.9782609 |
| 591 | 2 | 2 | 296 | F | Barcelona | Sweden | 1 | L | 244 | 10 | 6 | NA | 55 | 45 | 100 | NA | NA | NA |
| 592 | 2 | 2 | 296 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 601 | 3 | 1 | 301 | F | Barcelona | Barcelona | 1 | N | 260 | 10 | 22 | 1.102 | 24 | 34 | 58 | NA | NA | NA |
| 602 | 3 | 1 | 301 | M | Barcelona | Barcelona | 1 | N | 258 | 10 | 20 | 1.009 | NA | NA | NA | 50 | 0 | 1.0000000 |
| 603 | 3 | 1 | 302 | F | Brownsville | Barcelona | 1 | N | 259 | 10 | 21 | 0.988 | 0 | 0 | 0 | NA | NA | NA |
| 604 | 3 | 1 | 302 | M | Barcelona | Brownsville | 1 | N | 268 | 11 | 6 | NA | NA | NA | NA | 136 | 13 | 0.9127517 |
| 605 | 3 | 1 | 303 | F | Dahomey | Barcelona | 1 | N | 268 | 11 | 6 | NA | 0 | 0 | 0 | NA | NA | NA |
| 606 | 3 | 1 | 303 | M | Barcelona | Dahomey | 1 | N | 269 | 11 | 7 | 0.940 | NA | NA | NA | 0 | 26 | 0.0000000 |
| 607 | 3 | 1 | 304 | F | Israel | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 608 | 3 | 1 | 304 | M | Barcelona | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 609 | 3 | 1 | 305 | F | Sweden | Barcelona | 1 | N | 267 | 11 | 5 | 0.981 | 17 | 15 | 32 | NA | NA | NA |
| 610 | 3 | 1 | 305 | M | Barcelona | Sweden | 1 | N | 260 | 10 | 22 | 0.820 | NA | NA | NA | 96 | 0 | 1.0000000 |
| 611 | 3 | 1 | 306 | F | Barcelona | Brownsville | 1 | N | 249 | 10 | 11 | 1.202 | 40 | 41 | 81 | NA | NA | NA |
| 612 | 3 | 1 | 306 | M | Brownsville | Barcelona | 1 | N | 250 | 10 | 12 | NA | NA | NA | NA | 0 | 71 | 0.0000000 |
| 615 | 3 | 1 | 308 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 616 | 3 | 1 | 308 | M | Brownsville | Dahomey | 1 | P | 268 | 11 | 6 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 617 | 3 | 1 | 309 | F | Israel | Brownsville | 1 | N | 283 | 11 | 21 | 0.969 | 6 | 6 | 12 | NA | NA | NA |
| 618 | 3 | 1 | 309 | M | Brownsville | Israel | 1 | N | 252 | 10 | 14 | NA | NA | NA | NA | 0 | 25 | 0.0000000 |
| 619 | 3 | 1 | 310 | F | Sweden | Brownsville | 1 | N | 261 | 10 | 23 | NA | 0 | 0 | 0 | NA | NA | NA |
| 620 | 3 | 1 | 310 | M | Brownsville | Sweden | 1 | N | 261 | 10 | 23 | 0.936 | NA | NA | NA | 0 | 73 | 0.0000000 |
| 621 | 3 | 1 | 311 | F | Barcelona | Dahomey | 1 | N | 267 | 11 | 5 | 0.811 | 9 | 11 | 20 | NA | NA | NA |
| 622 | 3 | 1 | 311 | M | Dahomey | Barcelona | 1 | N | 264 | 11 | 2 | NA | NA | NA | NA | 6 | 69 | 0.0800000 |
| 623 | 3 | 1 | 312 | F | Brownsville | Dahomey | 1 | N | 266 | 11 | 4 | NA | 19 | 17 | 36 | NA | NA | NA |
| 624 | 3 | 1 | 312 | M | Dahomey | Brownsville | 1 | N | 266 | 11 | 4 | 0.840 | NA | NA | NA | 45 | 1 | 0.9782609 |
| 625 | 3 | 1 | 313 | F | Dahomey | Dahomey | 1 | N | 246 | 10 | 8 | 1.264 | 40 | 31 | 71 | NA | NA | NA |
| 626 | 3 | 1 | 313 | M | Dahomey | Dahomey | 1 | N | 268 | 11 | 6 | 0.957 | NA | NA | NA | 0 | 120 | 0.0000000 |
| 627 | 3 | 1 | 314 | F | Israel | Dahomey | 1 | N | 265 | 11 | 3 | NA | 13 | 19 | 32 | NA | NA | NA |
| 628 | 3 | 1 | 314 | M | Dahomey | Israel | 1 | N | 273 | 11 | 11 | NA | NA | NA | NA | 42 | 21 | 0.6666667 |
| 629 | 3 | 1 | 315 | F | Sweden | Dahomey | 1 | N | 246 | 10 | 8 | 1.179 | 13 | 12 | 25 | NA | NA | NA |
| 630 | 3 | 1 | 315 | M | Dahomey | Sweden | 1 | N | 245 | 10 | 7 | 1.102 | NA | NA | NA | 67 | 0 | 1.0000000 |
| 631 | 3 | 1 | 316 | F | Barcelona | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 632 | 3 | 1 | 316 | M | Israel | Barcelona | 1 | P | 248 | 10 | 10 | 1.179 | NA | NA | NA | 90 | 0 | 1.0000000 |
| 633 | 3 | 1 | 317 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 634 | 3 | 1 | 317 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 635 | 3 | 1 | 318 | F | Dahomey | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 636 | 3 | 1 | 318 | M | Israel | Dahomey | 1 | P | 252 | 10 | 14 | 1.014 | NA | NA | NA | 72 | 17 | 0.8089888 |
| 637 | 3 | 1 | 319 | F | Israel | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 638 | 3 | 1 | 319 | M | Israel | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 639 | 3 | 1 | 320 | F | Sweden | Israel | 1 | N | NA | NA | NA | 1.194 | 25 | 21 | 46 | NA | NA | NA |
| 640 | 3 | 1 | 320 | M | Israel | Sweden | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 641 | 3 | 1 | 321 | F | Barcelona | Sweden | 1 | N | 258 | 10 | 20 | NA | 28 | 20 | 48 | NA | NA | NA |
| 642 | 3 | 1 | 321 | M | Sweden | Barcelona | 1 | N | 260 | 10 | 22 | 1.030 | NA | NA | NA | 140 | 0 | 1.0000000 |
| 643 | 3 | 1 | 322 | F | Brownsville | Sweden | 1 | N | 252 | 10 | 14 | 1.083 | 23 | 22 | 45 | NA | NA | NA |
| 644 | 3 | 1 | 322 | M | Sweden | Brownsville | 1 | N | 270 | 11 | 8 | 0.926 | NA | NA | NA | 0 | 103 | 0.0000000 |
| 645 | 3 | 1 | 323 | F | Dahomey | Sweden | 1 | L | 246 | 10 | 8 | 1.287 | 0 | 0 | 0 | NA | NA | NA |
| 646 | 3 | 1 | 323 | M | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 647 | 3 | 1 | 324 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 648 | 3 | 1 | 324 | M | Sweden | Israel | 1 | P | 246 | 10 | 8 | 1.139 | NA | NA | NA | 44 | 0 | 1.0000000 |
| 649 | 3 | 1 | 325 | F | Sweden | Sweden | 1 | N | 244 | 10 | 6 | 1.163 | 26 | 32 | 58 | NA | NA | NA |
| 650 | 3 | 1 | 325 | M | Sweden | Sweden | 1 | N | 287 | 12 | 1 | 0.951 | NA | NA | NA | 0 | 52 | 0.0000000 |
| 651 | 3 | 1 | 326 | F | Barcelona | Barcelona | 1 | P | 260 | 10 | 22 | 1.020 | 35 | 19 | 54 | NA | NA | NA |
| 652 | 3 | 1 | 326 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 653 | 3 | 1 | 327 | F | Brownsville | Barcelona | 1 | P | 256 | 10 | 18 | 1.142 | 29 | 29 | 58 | NA | NA | NA |
| 654 | 3 | 1 | 327 | M | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 655 | 3 | 1 | 328 | F | Dahomey | Barcelona | 1 | N | 254 | 10 | 16 | 1.176 | 13 | 34 | 47 | NA | NA | NA |
| 656 | 3 | 1 | 328 | M | Barcelona | Dahomey | 1 | N | 264 | 11 | 2 | 0.982 | NA | NA | NA | 119 | 0 | 1.0000000 |
| 657 | 3 | 1 | 329 | F | Israel | Barcelona | 1 | N | 273 | 11 | 11 | 1.108 | 0 | 0 | 0 | NA | NA | NA |
| 658 | 3 | 1 | 329 | M | Barcelona | Israel | 1 | N | 267 | 11 | 5 | 1.033 | NA | NA | NA | 0 | 59 | 0.0000000 |
| 661 | 3 | 1 | 331 | F | Barcelona | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 662 | 3 | 1 | 331 | M | Brownsville | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 663 | 3 | 1 | 332 | F | Brownsville | Brownsville | 1 | N | 265 | 11 | 3 | 1.039 | 5 | 4 | 9 | NA | NA | NA |
| 664 | 3 | 1 | 332 | M | Brownsville | Brownsville | 1 | N | 268 | 11 | 6 | 1.012 | NA | NA | NA | 0 | 72 | 0.0000000 |
| 665 | 3 | 1 | 333 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 666 | 3 | 1 | 333 | M | Brownsville | Dahomey | 1 | P | 250 | 10 | 12 | 1.050 | NA | NA | NA | 0 | 0 | 0.0000000 |
| 667 | 3 | 1 | 334 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 668 | 3 | 1 | 334 | M | Brownsville | Israel | 1 | L | 243 | 10 | 5 | 1.009 | NA | NA | NA | 0 | 32 | 0.0000000 |
| 669 | 3 | 1 | 335 | F | Sweden | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 670 | 3 | 1 | 335 | M | Brownsville | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 671 | 3 | 1 | 336 | F | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 672 | 3 | 1 | 336 | M | Dahomey | Barcelona | 1 | P | 273 | 11 | 11 | NA | NA | NA | NA | 0 | 57 | 0.0000000 |
| 673 | 3 | 1 | 337 | F | Brownsville | Dahomey | 1 | N | 248 | 10 | 10 | NA | 27 | 24 | 51 | NA | NA | NA |
| 674 | 3 | 1 | 337 | M | Dahomey | Brownsville | 1 | N | 253 | 10 | 15 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 675 | 3 | 1 | 338 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 676 | 3 | 1 | 338 | M | Dahomey | Dahomey | 1 | P | 273 | 11 | 11 | 0.964 | NA | NA | NA | 0 | 76 | 0.0000000 |
| 677 | 3 | 1 | 339 | F | Israel | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 678 | 3 | 1 | 339 | M | Dahomey | Israel | 1 | P | 266 | 11 | 4 | 1.030 | NA | NA | NA | 86 | 4 | 0.9555556 |
| 679 | 3 | 1 | 340 | F | Sweden | Dahomey | 1 | N | 248 | 10 | 10 | NA | 0 | 0 | 0 | NA | NA | NA |
| 680 | 3 | 1 | 340 | M | Dahomey | Sweden | 1 | N | 258 | 10 | 20 | NA | NA | NA | NA | 0 | 48 | 0.0000000 |
| 681 | 3 | 1 | 341 | F | Barcelona | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 682 | 3 | 1 | 341 | M | Israel | Barcelona | 1 | P | 262 | 10 | 0 | 1.050 | NA | NA | NA | 83 | 5 | 0.9431818 |
| 683 | 3 | 1 | 342 | F | Brownsville | Israel | 1 | N | 261 | 10 | 23 | 1.084 | 22 | 23 | 45 | NA | NA | NA |
| 684 | 3 | 1 | 342 | M | Israel | Brownsville | 1 | N | 261 | 10 | 23 | 0.975 | NA | NA | NA | 69 | 0 | 1.0000000 |
| 685 | 3 | 1 | 343 | F | Dahomey | Israel | 1 | N | 259 | 10 | 21 | 1.155 | 0 | 0 | 0 | NA | NA | NA |
| 686 | 3 | 1 | 343 | M | Israel | Dahomey | 1 | N | 283 | 11 | 21 | 0.931 | NA | NA | NA | 0 | 40 | 0.0000000 |
| 687 | 3 | 1 | 344 | F | Israel | Israel | 1 | N | 269 | 11 | 7 | NA | 0 | 0 | 0 | NA | NA | NA |
| 688 | 3 | 1 | 344 | M | Israel | Israel | 1 | N | 276 | 11 | 14 | 1.060 | NA | NA | NA | 138 | 0 | 1.0000000 |
| 689 | 3 | 1 | 345 | F | Sweden | Israel | 1 | N | 271 | 11 | 9 | 1.038 | 14 | 15 | 29 | NA | NA | NA |
| 690 | 3 | 1 | 345 | M | Israel | Sweden | 1 | N | 274 | 11 | 12 | 1.032 | NA | NA | NA | 30 | 6 | 0.8333333 |
| 691 | 3 | 1 | 346 | F | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 692 | 3 | 1 | 346 | M | Sweden | Barcelona | 1 | P | 266 | 11 | 4 | 1.035 | NA | NA | NA | 0 | 47 | 0.0000000 |
| 693 | 3 | 1 | 347 | F | Brownsville | Sweden | 1 | N | 259 | 10 | 21 | 1.106 | 36 | 24 | 60 | NA | NA | NA |
| 694 | 3 | 1 | 347 | M | Sweden | Brownsville | 1 | N | 253 | 10 | 15 | 1.054 | NA | NA | NA | 53 | 6 | 0.8983051 |
| 695 | 3 | 1 | 348 | F | Dahomey | Sweden | 1 | N | 270 | 11 | 8 | NA | 0 | 0 | 0 | NA | NA | NA |
| 696 | 3 | 1 | 348 | M | Sweden | Dahomey | 1 | N | 261 | 10 | 23 | 1.074 | NA | NA | NA | 0 | 37 | 0.0000000 |
| 697 | 3 | 1 | 349 | F | Israel | Sweden | 1 | N | 275 | 11 | 13 | 1.167 | 32 | 28 | 60 | NA | NA | NA |
| 698 | 3 | 1 | 349 | M | Sweden | Israel | 1 | N | 288 | 12 | 2 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 699 | 3 | 1 | 350 | F | Sweden | Sweden | 1 | N | 249 | 10 | 11 | 1.111 | 30 | 26 | 56 | NA | NA | NA |
| 700 | 3 | 1 | 350 | M | Sweden | Sweden | 1 | N | 270 | 11 | 8 | 1.072 | NA | NA | NA | 85 | 17 | 0.8333333 |
| 701 | 3 | 1 | 351 | F | Barcelona | Barcelona | 1 | P | 262 | 10 | 0 | NA | NA | NA | NA | NA | NA | NA |
| 702 | 3 | 1 | 351 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 703 | 3 | 1 | 352 | F | Brownsville | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 704 | 3 | 1 | 352 | M | Barcelona | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 705 | 3 | 1 | 353 | F | Dahomey | Barcelona | 1 | N | 247 | 10 | 9 | 1.113 | 15 | 14 | 29 | NA | NA | NA |
| 706 | 3 | 1 | 353 | M | Barcelona | Dahomey | 1 | N | 267 | 11 | 5 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 707 | 3 | 1 | 354 | F | Israel | Barcelona | 1 | N | 258 | 10 | 20 | 1.210 | 29 | 18 | 47 | NA | NA | NA |
| 708 | 3 | 1 | 354 | M | Barcelona | Israel | 1 | N | 261 | 10 | 23 | 1.137 | NA | NA | NA | 50 | 0 | 1.0000000 |
| 709 | 3 | 1 | 355 | F | Sweden | Barcelona | 1 | N | 252 | 10 | 14 | 1.057 | 26 | 23 | 49 | NA | NA | NA |
| 710 | 3 | 1 | 355 | M | Barcelona | Sweden | 1 | N | 249 | 10 | 11 | 1.060 | NA | NA | NA | 71 | 13 | 0.8452381 |
| 711 | 3 | 1 | 356 | F | Barcelona | Brownsville | 1 | N | 267 | 11 | 5 | 1.074 | 38 | 35 | 73 | NA | NA | NA |
| 712 | 3 | 1 | 356 | M | Brownsville | Barcelona | 1 | N | 256 | 10 | 18 | 1.082 | NA | NA | NA | 0 | 87 | 0.0000000 |
| 713 | 3 | 1 | 357 | F | Brownsville | Brownsville | 1 | L | 268 | 11 | 6 | NA | NA | NA | NA | NA | NA | NA |
| 714 | 3 | 1 | 357 | M | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 715 | 3 | 1 | 358 | F | Dahomey | Brownsville | 1 | N | 246 | 10 | 8 | 1.220 | 0 | 0 | 0 | NA | NA | NA |
| 716 | 3 | 1 | 358 | M | Brownsville | Dahomey | 1 | N | 249 | 10 | 11 | 1.094 | NA | NA | NA | 0 | 45 | 0.0000000 |
| 717 | 3 | 1 | 359 | F | Israel | Brownsville | 1 | P | 265 | 11 | 3 | 1.105 | 0 | 0 | 0 | NA | NA | NA |
| 718 | 3 | 1 | 359 | M | Brownsville | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 719 | 3 | 1 | 360 | F | Sweden | Brownsville | 1 | L | 247 | 10 | 9 | 1.285 | NA | NA | NA | NA | NA | NA |
| 720 | 3 | 1 | 360 | M | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 721 | 3 | 1 | 361 | F | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 722 | 3 | 1 | 361 | M | Dahomey | Barcelona | 1 | P | 258 | 10 | 20 | 1.071 | NA | NA | NA | 151 | 1 | 0.9934211 |
| 723 | 3 | 1 | 362 | F | Brownsville | Dahomey | 1 | N | 255 | 10 | 17 | 1.178 | 5 | 5 | 10 | NA | NA | NA |
| 724 | 3 | 1 | 362 | M | Dahomey | Brownsville | 1 | N | 254 | 10 | 16 | 1.087 | NA | NA | NA | 150 | 2 | 0.9868421 |
| 725 | 3 | 1 | 363 | F | Dahomey | Dahomey | 1 | N | 293 | 12 | 7 | 1.052 | 21 | 32 | 53 | NA | NA | NA |
| 726 | 3 | 1 | 363 | M | Dahomey | Dahomey | 1 | N | 270 | 11 | 8 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 727 | 3 | 1 | 364 | F | Israel | Dahomey | 1 | L | 265 | 11 | 3 | 1.233 | 44 | 32 | 76 | NA | NA | NA |
| 728 | 3 | 1 | 364 | M | Dahomey | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 729 | 3 | 1 | 365 | F | Sweden | Dahomey | 1 | N | 266 | 11 | 4 | NA | 20 | 14 | 34 | NA | NA | NA |
| 730 | 3 | 1 | 365 | M | Dahomey | Sweden | 1 | N | 247 | 10 | 9 | 1.060 | NA | NA | NA | 112 | 30 | 0.7887324 |
| 731 | 3 | 1 | 366 | F | Barcelona | Israel | 1 | N | 260 | 10 | 22 | 1.179 | 0 | 0 | 0 | NA | NA | NA |
| 732 | 3 | 1 | 366 | M | Israel | Barcelona | 1 | N | 264 | 11 | 2 | 1.038 | NA | NA | NA | 0 | 0 | 0.0000000 |
| 733 | 3 | 1 | 367 | F | Brownsville | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 734 | 3 | 1 | 367 | M | Israel | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 735 | 3 | 1 | 368 | F | Dahomey | Israel | 1 | P | 262 | 10 | 0 | 1.106 | 26 | 25 | 51 | NA | NA | NA |
| 736 | 3 | 1 | 368 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 737 | 3 | 1 | 369 | F | Israel | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 738 | 3 | 1 | 369 | M | Israel | Israel | 1 | P | 256 | 10 | 18 | 1.134 | NA | NA | NA | 1 | 3 | 0.2500000 |
| 739 | 3 | 1 | 370 | F | Sweden | Israel | 1 | L | 259 | 10 | 21 | 1.214 | 8 | 18 | 26 | NA | NA | NA |
| 740 | 3 | 1 | 370 | M | Israel | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 741 | 3 | 1 | 371 | F | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 742 | 3 | 1 | 371 | M | Sweden | Barcelona | 1 | L | 257 | 10 | 19 | 1.005 | NA | NA | NA | 73 | 36 | 0.6697248 |
| 743 | 3 | 1 | 372 | F | Brownsville | Sweden | 1 | N | 263 | 10 | 1 | 1.057 | 31 | 21 | 52 | NA | NA | NA |
| 744 | 3 | 1 | 372 | M | Sweden | Brownsville | 1 | N | 270 | 11 | 8 | 0.928 | NA | NA | NA | 0 | 11 | 0.0000000 |
| 745 | 3 | 1 | 373 | F | Dahomey | Sweden | 1 | N | 262 | 10 | 0 | 1.068 | 24 | 28 | 52 | NA | NA | NA |
| 746 | 3 | 1 | 373 | M | Sweden | Dahomey | 1 | N | 271 | 11 | 9 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 747 | 3 | 1 | 374 | F | Israel | Sweden | 1 | N | 278 | 11 | 16 | 1.133 | 27 | 30 | 57 | NA | NA | NA |
| 748 | 3 | 1 | 374 | M | Sweden | Israel | 1 | N | 261 | 10 | 23 | NA | NA | NA | NA | 59 | 109 | 0.3511905 |
| 749 | 3 | 1 | 375 | F | Sweden | Sweden | 1 | P | 268 | 11 | 6 | 1.140 | 38 | 31 | 69 | NA | NA | NA |
| 750 | 3 | 1 | 375 | M | Sweden | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 751 | 3 | 1 | 376 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 752 | 3 | 1 | 376 | M | Barcelona | Barcelona | 1 | P | 268 | 11 | 6 | 0.926 | NA | NA | NA | 0 | 19 | 0.0000000 |
| 753 | 3 | 1 | 377 | F | Brownsville | Barcelona | 1 | L | 243 | 10 | 5 | 1.369 | 0 | 0 | 0 | NA | NA | NA |
| 754 | 3 | 1 | 377 | M | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 755 | 3 | 1 | 378 | F | Dahomey | Barcelona | 1 | P | 264 | 11 | 2 | NA | 0 | 0 | 0 | NA | NA | NA |
| 756 | 3 | 1 | 378 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 757 | 3 | 1 | 379 | F | Israel | Barcelona | 1 | N | 262 | 10 | 0 | 1.202 | 31 | 37 | 68 | NA | NA | NA |
| 758 | 3 | 1 | 379 | M | Barcelona | Israel | 1 | N | 285 | 11 | 23 | 1.016 | NA | NA | NA | 0 | 32 | 0.0000000 |
| 759 | 3 | 1 | 380 | F | Sweden | Barcelona | 1 | N | 253 | 10 | 15 | NA | 0 | 0 | 0 | NA | NA | NA |
| 760 | 3 | 1 | 380 | M | Barcelona | Sweden | 1 | N | 289 | 12 | 3 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 761 | 3 | 1 | 381 | F | Barcelona | Brownsville | 1 | L | 259 | 10 | 21 | 1.303 | 47 | 53 | 100 | NA | NA | NA |
| 762 | 3 | 1 | 381 | M | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 763 | 3 | 1 | 382 | F | Brownsville | Brownsville | 1 | P | 262 | 10 | 0 | NA | 24 | 11 | 35 | NA | NA | NA |
| 764 | 3 | 1 | 382 | M | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 765 | 3 | 1 | 383 | F | Dahomey | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 766 | 3 | 1 | 383 | M | Brownsville | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 767 | 3 | 1 | 384 | F | Israel | Brownsville | 1 | N | 273 | 11 | 11 | 1.174 | 0 | 0 | 0 | NA | NA | NA |
| 768 | 3 | 1 | 384 | M | Brownsville | Israel | 1 | N | 274 | 11 | 12 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 769 | 3 | 1 | 385 | F | Sweden | Brownsville | 1 | N | NA | NA | NA | 1.086 | 27 | 29 | 56 | NA | NA | NA |
| 770 | 3 | 1 | 385 | M | Brownsville | Sweden | 1 | N | NA | NA | NA | 0.969 | NA | NA | NA | 0 | 11 | 0.0000000 |
| 771 | 3 | 1 | 386 | F | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 772 | 3 | 1 | 386 | M | Dahomey | Barcelona | 1 | P | 287 | 12 | 1 | NA | NA | NA | NA | 0 | 65 | 0.0000000 |
| 773 | 3 | 1 | 387 | F | Brownsville | Dahomey | 1 | P | 262 | 10 | 0 | 1.166 | 37 | 27 | 64 | NA | NA | NA |
| 774 | 3 | 1 | 387 | M | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 775 | 3 | 1 | 388 | F | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 776 | 3 | 1 | 388 | M | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 777 | 3 | 1 | 389 | F | Israel | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 778 | 3 | 1 | 389 | M | Dahomey | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 781 | 3 | 1 | 391 | F | Barcelona | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 782 | 3 | 1 | 391 | M | Israel | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 783 | 3 | 1 | 392 | F | Brownsville | Israel | 1 | N | 255 | 10 | 17 | 1.190 | 0 | 0 | 0 | NA | NA | NA |
| 784 | 3 | 1 | 392 | M | Israel | Brownsville | 1 | N | 266 | 11 | 4 | NA | NA | NA | NA | 0 | 63 | 0.0000000 |
| 785 | 3 | 1 | 393 | F | Dahomey | Israel | 1 | P | 260 | 10 | 22 | 1.134 | 26 | 31 | 57 | NA | NA | NA |
| 786 | 3 | 1 | 393 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 787 | 3 | 1 | 394 | F | Israel | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 788 | 3 | 1 | 394 | M | Israel | Israel | 1 | P | 262 | 10 | 0 | 1.116 | NA | NA | NA | 92 | 2 | 0.9787234 |
| 789 | 3 | 1 | 395 | F | Sweden | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 790 | 3 | 1 | 395 | M | Israel | Sweden | 1 | P | 273 | 11 | 11 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 793 | 3 | 1 | 397 | F | Brownsville | Sweden | 1 | L | 262 | 10 | 0 | 1.183 | 13 | 0 | 13 | NA | NA | NA |
| 794 | 3 | 1 | 397 | M | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 795 | 3 | 1 | 398 | F | Dahomey | Sweden | 1 | P | 274 | 11 | 12 | 0.940 | 27 | 29 | 56 | NA | NA | NA |
| 796 | 3 | 1 | 398 | M | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 797 | 3 | 1 | 399 | F | Israel | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 798 | 3 | 1 | 399 | M | Sweden | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 799 | 3 | 1 | 400 | F | Sweden | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 800 | 3 | 1 | 400 | M | Sweden | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 801 | 3 | 2 | 401 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 802 | 3 | 2 | 401 | M | Barcelona | Barcelona | 1 | P | 255 | 10 | 17 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 803 | 3 | 2 | 402 | F | Brownsville | Barcelona | 1 | N | 244 | 10 | 6 | 1.108 | 23 | 20 | 43 | NA | NA | NA |
| 804 | 3 | 2 | 402 | M | Barcelona | Brownsville | 1 | N | 249 | 10 | 11 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 805 | 3 | 2 | 403 | F | Dahomey | Barcelona | 1 | L | 265 | 11 | 3 | 1.024 | 26 | 29 | 55 | NA | NA | NA |
| 806 | 3 | 2 | 403 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 807 | 3 | 2 | 404 | F | Israel | Barcelona | 1 | N | 265 | 11 | 3 | 1.015 | 20 | 18 | 38 | NA | NA | NA |
| 808 | 3 | 2 | 404 | M | Barcelona | Israel | 1 | N | 264 | 11 | 2 | 0.955 | NA | NA | NA | 119 | 0 | 1.0000000 |
| 809 | 3 | 2 | 405 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 810 | 3 | 2 | 405 | M | Barcelona | Sweden | 1 | P | 266 | 11 | 4 | 0.956 | NA | NA | NA | 0 | 35 | 0.0000000 |
| 811 | 3 | 2 | 406 | F | Barcelona | Brownsville | 1 | P | 263 | 10 | 1 | 1.119 | 18 | 8 | 26 | NA | NA | NA |
| 812 | 3 | 2 | 406 | M | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 813 | 3 | 2 | 407 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 814 | 3 | 2 | 407 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 815 | 3 | 2 | 408 | F | Dahomey | Brownsville | 1 | P | 245 | 10 | 7 | 1.143 | 31 | 32 | 63 | NA | NA | NA |
| 816 | 3 | 2 | 408 | M | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 817 | 3 | 2 | 409 | F | Israel | Brownsville | 1 | N | 258 | 10 | 20 | 1.172 | 37 | 34 | 71 | NA | NA | NA |
| 818 | 3 | 2 | 409 | M | Brownsville | Israel | 1 | N | 269 | 11 | 7 | 1.025 | NA | NA | NA | 67 | 44 | 0.6036036 |
| 819 | 3 | 2 | 410 | F | Sweden | Brownsville | 1 | N | 262 | 10 | 0 | 1.183 | 20 | 20 | 40 | NA | NA | NA |
| 820 | 3 | 2 | 410 | M | Brownsville | Sweden | 1 | N | 261 | 10 | 23 | 1.006 | NA | NA | NA | 96 | 0 | 1.0000000 |
| 821 | 3 | 2 | 411 | F | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 822 | 3 | 2 | 411 | M | Dahomey | Barcelona | 1 | P | 257 | 10 | 19 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 823 | 3 | 2 | 412 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 824 | 3 | 2 | 412 | M | Dahomey | Brownsville | 1 | P | 255 | 10 | 17 | 1.068 | NA | NA | NA | 32 | 2 | 0.9411765 |
| 825 | 3 | 2 | 413 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 826 | 3 | 2 | 413 | M | Dahomey | Dahomey | 1 | L | 263 | 10 | 1 | NA | NA | NA | NA | 8 | 20 | 0.2857143 |
| 827 | 3 | 2 | 414 | F | Israel | Dahomey | 1 | N | 242 | 10 | 4 | 1.094 | 23 | 31 | 54 | NA | NA | NA |
| 828 | 3 | 2 | 414 | M | Dahomey | Israel | 1 | N | 262 | 10 | 0 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 829 | 3 | 2 | 415 | F | Sweden | Dahomey | 1 | N | 272 | 11 | 10 | NA | 0 | 0 | 0 | NA | NA | NA |
| 830 | 3 | 2 | 415 | M | Dahomey | Sweden | 1 | N | 263 | 10 | 1 | 1.023 | NA | NA | NA | 121 | 2 | 0.9837398 |
| 831 | 3 | 2 | 416 | F | Barcelona | Israel | 1 | N | 276 | 11 | 14 | 1.123 | 27 | 31 | 58 | NA | NA | NA |
| 832 | 3 | 2 | 416 | M | Israel | Barcelona | 1 | N | 251 | 10 | 13 | 1.055 | NA | NA | NA | 83 | 68 | 0.5496689 |
| 833 | 3 | 2 | 417 | F | Brownsville | Israel | 1 | N | 285 | 11 | 23 | 1.013 | 12 | 30 | 42 | NA | NA | NA |
| 834 | 3 | 2 | 417 | M | Israel | Brownsville | 1 | N | 261 | 10 | 23 | NA | NA | NA | NA | 58 | 0 | 1.0000000 |
| 835 | 3 | 2 | 418 | F | Dahomey | Israel | 1 | L | 271 | 11 | 9 | 1.137 | 27 | 23 | 50 | NA | NA | NA |
| 836 | 3 | 2 | 418 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 837 | 3 | 2 | 419 | F | Israel | Israel | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 838 | 3 | 2 | 419 | M | Israel | Israel | 1 | N | 259 | 10 | 21 | 0.977 | NA | NA | NA | 0 | 45 | 0.0000000 |
| 839 | 3 | 2 | 420 | F | Sweden | Israel | 1 | N | 267 | 11 | 5 | 1.022 | 12 | 23 | 35 | NA | NA | NA |
| 840 | 3 | 2 | 420 | M | Israel | Sweden | 1 | N | 258 | 10 | 20 | 1.017 | NA | NA | NA | 76 | 0 | 1.0000000 |
| 841 | 3 | 2 | 421 | F | Barcelona | Sweden | 1 | N | 257 | 10 | 19 | NA | 0 | 0 | 0 | NA | NA | NA |
| 842 | 3 | 2 | 421 | M | Sweden | Barcelona | 1 | N | 258 | 10 | 20 | NA | NA | NA | NA | 119 | 0 | 1.0000000 |
| 843 | 3 | 2 | 422 | F | Brownsville | Sweden | 1 | N | 264 | 11 | 2 | 1.133 | 15 | 18 | 33 | NA | NA | NA |
| 844 | 3 | 2 | 422 | M | Sweden | Brownsville | 1 | N | NA | NA | NA | 0.938 | NA | NA | NA | 0 | 40 | 0.0000000 |
| 845 | 3 | 2 | 423 | F | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 846 | 3 | 2 | 423 | M | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 847 | 3 | 2 | 424 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 848 | 3 | 2 | 424 | M | Sweden | Israel | 1 | L | 283 | 11 | 21 | 0.875 | NA | NA | NA | 0 | 56 | 0.0000000 |
| 849 | 3 | 2 | 425 | F | Sweden | Sweden | 1 | N | 247 | 10 | 9 | NA | 0 | 0 | 0 | NA | NA | NA |
| 850 | 3 | 2 | 425 | M | Sweden | Sweden | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 851 | 3 | 2 | 426 | F | Barcelona | Barcelona | 1 | L | 267 | 11 | 5 | NA | 37 | 20 | 57 | NA | NA | NA |
| 852 | 3 | 2 | 426 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 855 | 3 | 2 | 428 | F | Dahomey | Barcelona | 1 | L | 247 | 10 | 9 | 1.175 | 35 | 30 | 65 | NA | NA | NA |
| 856 | 3 | 2 | 428 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 857 | 3 | 2 | 429 | F | Israel | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 858 | 3 | 2 | 429 | M | Barcelona | Israel | 1 | L | 263 | 10 | 1 | 1.051 | NA | NA | NA | 93 | 15 | 0.8611111 |
| 859 | 3 | 2 | 430 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 860 | 3 | 2 | 430 | M | Barcelona | Sweden | 1 | P | 268 | 11 | 6 | 0.949 | NA | NA | NA | 0 | 115 | 0.0000000 |
| 861 | 3 | 2 | 431 | F | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 862 | 3 | 2 | 431 | M | Brownsville | Barcelona | 1 | P | 268 | 11 | 6 | 1.033 | NA | NA | NA | 0 | 94 | 0.0000000 |
| 863 | 3 | 2 | 432 | F | Brownsville | Brownsville | 1 | P | 249 | 10 | 11 | NA | 0 | 0 | 0 | NA | NA | NA |
| 864 | 3 | 2 | 432 | M | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 865 | 3 | 2 | 433 | F | Dahomey | Brownsville | 1 | N | 250 | 10 | 12 | NA | 38 | 38 | 76 | NA | NA | NA |
| 866 | 3 | 2 | 433 | M | Brownsville | Dahomey | 1 | N | 263 | 10 | 1 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 867 | 3 | 2 | 434 | F | Israel | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 868 | 3 | 2 | 434 | M | Brownsville | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 869 | 3 | 2 | 435 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 870 | 3 | 2 | 435 | M | Brownsville | Sweden | 1 | P | 263 | 10 | 1 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 871 | 3 | 2 | 436 | F | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 872 | 3 | 2 | 436 | M | Dahomey | Barcelona | 1 | P | 249 | 10 | 11 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 873 | 3 | 2 | 437 | F | Brownsville | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 874 | 3 | 2 | 437 | M | Dahomey | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 875 | 3 | 2 | 438 | F | Dahomey | Dahomey | 1 | N | 249 | 10 | 11 | NA | 0 | 0 | 0 | NA | NA | NA |
| 876 | 3 | 2 | 438 | M | Dahomey | Dahomey | 1 | N | 248 | 10 | 10 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 877 | 3 | 2 | 439 | F | Israel | Dahomey | 1 | N | 264 | 11 | 2 | NA | 0 | 0 | 0 | NA | NA | NA |
| 878 | 3 | 2 | 439 | M | Dahomey | Israel | 1 | N | 257 | 10 | 19 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 879 | 3 | 2 | 440 | F | Sweden | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 880 | 3 | 2 | 440 | M | Dahomey | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 881 | 3 | 2 | 441 | F | Barcelona | Israel | 1 | N | 252 | 10 | 14 | NA | 0 | 0 | 0 | NA | NA | NA |
| 882 | 3 | 2 | 441 | M | Israel | Barcelona | 1 | N | 248 | 10 | 10 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 883 | 3 | 2 | 442 | F | Brownsville | Israel | 1 | P | 247 | 10 | 9 | NA | 0 | 0 | 0 | NA | NA | NA |
| 884 | 3 | 2 | 442 | M | Israel | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 885 | 3 | 2 | 443 | F | Dahomey | Israel | 1 | N | 241 | 10 | 3 | 1.142 | 0 | 0 | 0 | NA | NA | NA |
| 886 | 3 | 2 | 443 | M | Israel | Dahomey | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 56 | 0.0000000 |
| 887 | 3 | 2 | 444 | F | Israel | Israel | 1 | N | 247 | 10 | 9 | NA | 0 | 0 | 0 | NA | NA | NA |
| 888 | 3 | 2 | 444 | M | Israel | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 889 | 3 | 2 | 445 | F | Sweden | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 890 | 3 | 2 | 445 | M | Israel | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 891 | 3 | 2 | 446 | F | Barcelona | Sweden | 1 | N | 263 | 10 | 1 | 1.052 | 29 | 26 | 55 | NA | NA | NA |
| 892 | 3 | 2 | 446 | M | Sweden | Barcelona | 1 | N | 263 | 10 | 1 | 1.004 | NA | NA | NA | 137 | 0 | 1.0000000 |
| 893 | 3 | 2 | 447 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 894 | 3 | 2 | 447 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 895 | 3 | 2 | 448 | F | Dahomey | Sweden | 1 | P | 264 | 11 | 2 | NA | 0 | 0 | 0 | NA | NA | NA |
| 896 | 3 | 2 | 448 | M | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 897 | 3 | 2 | 449 | F | Israel | Sweden | 1 | N | 255 | 10 | 17 | NA | 0 | 0 | 0 | NA | NA | NA |
| 898 | 3 | 2 | 449 | M | Sweden | Israel | 1 | N | 247 | 10 | 9 | 1.086 | NA | NA | NA | 95 | 12 | 0.8878505 |
| 899 | 3 | 2 | 450 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 900 | 3 | 2 | 450 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 901 | 3 | 2 | 451 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 902 | 3 | 2 | 451 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 903 | 3 | 2 | 452 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 904 | 3 | 2 | 452 | M | Barcelona | Brownsville | 1 | P | 287 | 12 | 1 | 0.913 | NA | NA | NA | 0 | 57 | 0.0000000 |
| 905 | 3 | 2 | 453 | F | Dahomey | Barcelona | 1 | P | 248 | 10 | 10 | 1.170 | 8 | 11 | 19 | NA | NA | NA |
| 906 | 3 | 2 | 453 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 907 | 3 | 2 | 454 | F | Israel | Barcelona | 1 | N | 261 | 10 | 23 | 1.252 | 51 | 42 | 93 | NA | NA | NA |
| 908 | 3 | 2 | 454 | M | Barcelona | Israel | 1 | N | 251 | 10 | 13 | NA | NA | NA | NA | 92 | 7 | 0.9292929 |
| 909 | 3 | 2 | 455 | F | Sweden | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 910 | 3 | 2 | 455 | M | Barcelona | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 911 | 3 | 2 | 456 | F | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 912 | 3 | 2 | 456 | M | Brownsville | Barcelona | 1 | P | 260 | 10 | 22 | 1.056 | NA | NA | NA | 67 | 11 | 0.8589744 |
| 913 | 3 | 2 | 457 | F | Brownsville | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 914 | 3 | 2 | 457 | M | Brownsville | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 915 | 3 | 2 | 458 | F | Dahomey | Brownsville | 1 | P | NA | NA | NA | 1.023 | 6 | 11 | 17 | NA | NA | NA |
| 916 | 3 | 2 | 458 | M | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 917 | 3 | 2 | 459 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 918 | 3 | 2 | 459 | M | Brownsville | Israel | 1 | P | 267 | 11 | 5 | 1.110 | NA | NA | NA | 50 | 18 | 0.7352941 |
| 919 | 3 | 2 | 460 | F | Sweden | Brownsville | 1 | P | 290 | 12 | 4 | 0.979 | 22 | 16 | 38 | NA | NA | NA |
| 920 | 3 | 2 | 460 | M | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 921 | 3 | 2 | 461 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 922 | 3 | 2 | 461 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 923 | 3 | 2 | 462 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 924 | 3 | 2 | 462 | M | Dahomey | Brownsville | 1 | P | 265 | 11 | 3 | 1.088 | NA | NA | NA | 0 | 21 | 0.0000000 |
| 925 | 3 | 2 | 463 | F | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 926 | 3 | 2 | 463 | M | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 927 | 3 | 2 | 464 | F | Israel | Dahomey | 1 | N | 290 | 12 | 4 | 0.955 | 37 | 23 | 60 | NA | NA | NA |
| 928 | 3 | 2 | 464 | M | Dahomey | Israel | 1 | N | 256 | 10 | 18 | 1.051 | NA | NA | NA | 15 | 18 | 0.4545455 |
| 929 | 3 | 2 | 465 | F | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 930 | 3 | 2 | 465 | M | Dahomey | Sweden | 1 | P | 259 | 10 | 21 | NA | NA | NA | NA | 2 | 25 | 0.0740741 |
| 931 | 3 | 2 | 466 | F | Barcelona | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 932 | 3 | 2 | 466 | M | Israel | Barcelona | 1 | P | 251 | 10 | 13 | 0.964 | NA | NA | NA | 69 | 0 | 1.0000000 |
| 933 | 3 | 2 | 467 | F | Brownsville | Israel | 1 | N | 267 | 11 | 5 | 1.126 | 29 | 27 | 56 | NA | NA | NA |
| 934 | 3 | 2 | 467 | M | Israel | Brownsville | 1 | N | 285 | 11 | 23 | 1.005 | NA | NA | NA | 0 | 28 | 0.0000000 |
| 935 | 3 | 2 | 468 | F | Dahomey | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 936 | 3 | 2 | 468 | M | Israel | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 937 | 3 | 2 | 469 | F | Israel | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 938 | 3 | 2 | 469 | M | Israel | Israel | 1 | P | 255 | 10 | 17 | 1.122 | NA | NA | NA | 83 | 29 | 0.7410714 |
| 939 | 3 | 2 | 470 | F | Sweden | Israel | 1 | P | 262 | 10 | 0 | 0.991 | 17 | 21 | 38 | NA | NA | NA |
| 940 | 3 | 2 | 470 | M | Israel | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 941 | 3 | 2 | 471 | F | Barcelona | Sweden | 1 | L | 262 | 10 | 0 | 1.204 | 31 | 39 | 70 | NA | NA | NA |
| 942 | 3 | 2 | 471 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 943 | 3 | 2 | 472 | F | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 944 | 3 | 2 | 472 | M | Sweden | Brownsville | 1 | P | 281 | 11 | 19 | 0.983 | NA | NA | NA | 0 | 24 | 0.0000000 |
| 945 | 3 | 2 | 473 | F | Dahomey | Sweden | 1 | P | 260 | 10 | 22 | 1.133 | 9 | 14 | 23 | NA | NA | NA |
| 946 | 3 | 2 | 473 | M | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 947 | 3 | 2 | 474 | F | Israel | Sweden | 1 | P | 256 | 10 | 18 | 1.217 | 29 | 38 | 67 | NA | NA | NA |
| 948 | 3 | 2 | 474 | M | Sweden | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 951 | 3 | 2 | 476 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 952 | 3 | 2 | 476 | M | Barcelona | Barcelona | 1 | P | 283 | 11 | 21 | NA | NA | NA | NA | 0 | 24 | 0.0000000 |
| 961 | 3 | 2 | 481 | F | Barcelona | Brownsville | 1 | N | 268 | 11 | 6 | 1.019 | 0 | 0 | 0 | NA | NA | NA |
| 962 | 3 | 2 | 481 | M | Brownsville | Barcelona | 1 | N | 262 | 10 | 0 | 0.965 | NA | NA | NA | 0 | 33 | 0.0000000 |
| 963 | 3 | 2 | 482 | F | Brownsville | Brownsville | 1 | N | 284 | 11 | 22 | NA | 21 | 24 | 45 | NA | NA | NA |
| 964 | 3 | 2 | 482 | M | Brownsville | Brownsville | 1 | N | 250 | 10 | 12 | 1.086 | NA | NA | NA | 48 | 10 | 0.8275862 |
| 965 | 3 | 2 | 483 | F | Dahomey | Brownsville | 1 | P | 270 | 11 | 8 | 0.986 | 23 | 35 | 58 | NA | NA | NA |
| 966 | 3 | 2 | 483 | M | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 967 | 3 | 2 | 484 | F | Israel | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 968 | 3 | 2 | 484 | M | Brownsville | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 969 | 3 | 2 | 485 | F | Sweden | Brownsville | 1 | P | 249 | 10 | 11 | NA | 0 | 0 | 0 | NA | NA | NA |
| 970 | 3 | 2 | 485 | M | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 971 | 3 | 2 | 486 | F | Barcelona | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 972 | 3 | 2 | 486 | M | Dahomey | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 973 | 3 | 2 | 487 | F | Brownsville | Dahomey | 1 | N | 266 | 11 | 4 | 1.133 | 0 | 0 | 0 | NA | NA | NA |
| 974 | 3 | 2 | 487 | M | Dahomey | Brownsville | 1 | N | 248 | 10 | 10 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 975 | 3 | 2 | 488 | F | Dahomey | Dahomey | 1 | N | 264 | 11 | 2 | 1.075 | 10 | 11 | 21 | NA | NA | NA |
| 976 | 3 | 2 | 488 | M | Dahomey | Dahomey | 1 | N | 265 | 11 | 3 | 0.992 | NA | NA | NA | 0 | 12 | 0.0000000 |
| 977 | 3 | 2 | 489 | F | Israel | Dahomey | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 978 | 3 | 2 | 489 | M | Dahomey | Israel | 1 | N | NA | NA | NA | 1.041 | NA | NA | NA | 89 | 18 | 0.8317757 |
| 979 | 3 | 2 | 490 | F | Sweden | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 980 | 3 | 2 | 490 | M | Dahomey | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 981 | 3 | 2 | 491 | F | Barcelona | Israel | 1 | N | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 982 | 3 | 2 | 491 | M | Israel | Barcelona | 1 | N | NA | NA | NA | 0.883 | NA | NA | NA | 0 | 42 | 0.0000000 |
| 983 | 3 | 2 | 492 | F | Brownsville | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 984 | 3 | 2 | 492 | M | Israel | Brownsville | 1 | P | 297 | 12 | 11 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 985 | 3 | 2 | 493 | F | Dahomey | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 986 | 3 | 2 | 493 | M | Israel | Dahomey | 1 | L | 264 | 11 | 2 | NA | NA | NA | NA | 107 | 0 | 1.0000000 |
| 987 | 3 | 2 | 494 | F | Israel | Israel | 1 | N | 272 | 11 | 10 | 1.110 | 26 | 23 | 49 | NA | NA | NA |
| 988 | 3 | 2 | 494 | M | Israel | Israel | 1 | N | 268 | 11 | 6 | 0.999 | NA | NA | NA | 47 | 1 | 0.9791667 |
| 989 | 3 | 2 | 495 | F | Sweden | Israel | 1 | L | 261 | 10 | 23 | 1.190 | 34 | 35 | 69 | NA | NA | NA |
| 990 | 3 | 2 | 495 | M | Israel | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1001 | 4 | 1 | 501 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1002 | 4 | 1 | 501 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1003 | 4 | 1 | 502 | F | Brownsville | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1004 | 4 | 1 | 502 | M | Barcelona | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1005 | 4 | 1 | 503 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1006 | 4 | 1 | 503 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1007 | 4 | 1 | 504 | F | Israel | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1008 | 4 | 1 | 504 | M | Barcelona | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1009 | 4 | 1 | 505 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1010 | 4 | 1 | 505 | M | Barcelona | Sweden | 1 | P | 247 | 10 | 9 | 0.939 | NA | NA | NA | 0 | 49 | 0.0000000 |
| 1011 | 4 | 1 | 506 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1012 | 4 | 1 | 506 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1013 | 4 | 1 | 507 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1014 | 4 | 1 | 507 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1015 | 4 | 1 | 508 | F | Dahomey | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1016 | 4 | 1 | 508 | M | Brownsville | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1017 | 4 | 1 | 509 | F | Israel | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1018 | 4 | 1 | 509 | M | Brownsville | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1019 | 4 | 1 | 510 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1020 | 4 | 1 | 510 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1021 | 4 | 1 | 511 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1022 | 4 | 1 | 511 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1023 | 4 | 1 | 512 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1024 | 4 | 1 | 512 | M | Dahomey | Brownsville | 1 | P | 246 | 10 | 8 | 0.879 | NA | NA | NA | 0 | 6 | 0.0000000 |
| 1025 | 4 | 1 | 513 | F | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1026 | 4 | 1 | 513 | M | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1027 | 4 | 1 | 514 | F | Israel | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1028 | 4 | 1 | 514 | M | Dahomey | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1029 | 4 | 1 | 515 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1030 | 4 | 1 | 515 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1031 | 4 | 1 | 516 | F | Barcelona | Israel | 1 | N | 246 | 10 | 8 | 1.001 | 13 | 13 | 26 | NA | NA | NA |
| 1032 | 4 | 1 | 516 | M | Israel | Barcelona | 1 | N | 248 | 10 | 10 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1033 | 4 | 1 | 517 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1034 | 4 | 1 | 517 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1035 | 4 | 1 | 518 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1036 | 4 | 1 | 518 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1037 | 4 | 1 | 519 | F | Israel | Israel | 1 | P | 246 | 10 | 8 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1038 | 4 | 1 | 519 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1039 | 4 | 1 | 520 | F | Sweden | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1040 | 4 | 1 | 520 | M | Israel | Sweden | 1 | L | NA | NA | NA | 1.059 | NA | NA | NA | 90 | 3 | 0.9677419 |
| 1041 | 4 | 1 | 521 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1042 | 4 | 1 | 521 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1043 | 4 | 1 | 522 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1044 | 4 | 1 | 522 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1045 | 4 | 1 | 523 | F | Dahomey | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1046 | 4 | 1 | 523 | M | Sweden | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1047 | 4 | 1 | 524 | F | Israel | Sweden | 1 | L | 247 | 10 | 9 | NA | 25 | 22 | 47 | NA | NA | NA |
| 1048 | 4 | 1 | 524 | M | Sweden | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1049 | 4 | 1 | 525 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1050 | 4 | 1 | 525 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1051 | 4 | 1 | 526 | F | Barcelona | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1052 | 4 | 1 | 526 | M | Barcelona | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1053 | 4 | 1 | 527 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1054 | 4 | 1 | 527 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1055 | 4 | 1 | 528 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1056 | 4 | 1 | 528 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1057 | 4 | 1 | 529 | F | Israel | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1058 | 4 | 1 | 529 | M | Barcelona | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1059 | 4 | 1 | 530 | F | Sweden | Barcelona | 1 | N | 271 | 11 | 9 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1060 | 4 | 1 | 530 | M | Barcelona | Sweden | 1 | N | 271 | 11 | 9 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1063 | 4 | 1 | 532 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1064 | 4 | 1 | 532 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1065 | 4 | 1 | 533 | F | Dahomey | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1066 | 4 | 1 | 533 | M | Brownsville | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1067 | 4 | 1 | 534 | F | Israel | Brownsville | 1 | L | 244 | 10 | 6 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1068 | 4 | 1 | 534 | M | Brownsville | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1069 | 4 | 1 | 535 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1070 | 4 | 1 | 535 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1071 | 4 | 1 | 536 | F | Barcelona | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1072 | 4 | 1 | 536 | M | Dahomey | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1073 | 4 | 1 | 537 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1074 | 4 | 1 | 537 | M | Dahomey | Brownsville | 1 | L | 244 | 10 | 6 | 1.130 | NA | NA | NA | NA | NA | 0.9756098 |
| 1075 | 4 | 1 | 538 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1076 | 4 | 1 | 538 | M | Dahomey | Dahomey | 1 | P | 240 | 10 | 2 | 1.055 | NA | NA | NA | 22 | 18 | 0.5500000 |
| 1077 | 4 | 1 | 539 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1078 | 4 | 1 | 539 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1079 | 4 | 1 | 540 | F | Sweden | Dahomey | 1 | L | NA | NA | NA | 0.870 | 21 | 14 | 35 | NA | NA | NA |
| 1080 | 4 | 1 | 540 | M | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1081 | 4 | 1 | 541 | F | Barcelona | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1082 | 4 | 1 | 541 | M | Israel | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1083 | 4 | 1 | 542 | F | Brownsville | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1084 | 4 | 1 | 542 | M | Israel | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1085 | 4 | 1 | 543 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1086 | 4 | 1 | 543 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1087 | 4 | 1 | 544 | F | Israel | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1088 | 4 | 1 | 544 | M | Israel | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1089 | 4 | 1 | 545 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1090 | 4 | 1 | 545 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1093 | 4 | 1 | 547 | F | Brownsville | Sweden | 1 | N | 253 | 10 | 15 | 0.982 | 20 | 22 | 42 | NA | NA | NA |
| 1094 | 4 | 1 | 547 | M | Sweden | Brownsville | 1 | N | 263 | 10 | 1 | 0.897 | NA | NA | NA | 0 | 43 | 0.0000000 |
| 1095 | 4 | 1 | 548 | F | Dahomey | Sweden | 1 | L | 263 | 10 | 1 | 1.042 | 23 | 31 | 54 | NA | NA | NA |
| 1096 | 4 | 1 | 548 | M | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1097 | 4 | 1 | 549 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1098 | 4 | 1 | 549 | M | Sweden | Israel | 1 | P | 264 | 11 | 2 | 0.890 | NA | NA | NA | NA | NA | 0.0000000 |
| 1099 | 4 | 1 | 550 | F | Sweden | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1100 | 4 | 1 | 550 | M | Sweden | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1101 | 4 | 1 | 551 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1102 | 4 | 1 | 551 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1103 | 4 | 1 | 552 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1104 | 4 | 1 | 552 | M | Barcelona | Brownsville | 1 | P | 247 | 10 | 9 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1105 | 4 | 1 | 553 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1106 | 4 | 1 | 553 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1107 | 4 | 1 | 554 | F | Israel | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1108 | 4 | 1 | 554 | M | Barcelona | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1109 | 4 | 1 | 555 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1110 | 4 | 1 | 555 | M | Barcelona | Sweden | 1 | P | 264 | 11 | 2 | 0.882 | NA | NA | NA | 0 | 32 | 0.0000000 |
| 1111 | 4 | 1 | 556 | F | Barcelona | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1112 | 4 | 1 | 556 | M | Brownsville | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1113 | 4 | 1 | 557 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1114 | 4 | 1 | 557 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1115 | 4 | 1 | 558 | F | Dahomey | Brownsville | 1 | N | 244 | 10 | 6 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1116 | 4 | 1 | 558 | M | Brownsville | Dahomey | 1 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1117 | 4 | 1 | 559 | F | Israel | Brownsville | 1 | L | NA | NA | NA | 1.125 | 32 | 25 | 57 | NA | NA | NA |
| 1118 | 4 | 1 | 559 | M | Brownsville | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1119 | 4 | 1 | 560 | F | Sweden | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1120 | 4 | 1 | 560 | M | Brownsville | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1121 | 4 | 1 | 561 | F | Barcelona | Dahomey | 1 | L | 263 | 10 | 1 | 0.955 | 21 | 26 | 47 | NA | NA | NA |
| 1122 | 4 | 1 | 561 | M | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1123 | 4 | 1 | 562 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1124 | 4 | 1 | 562 | M | Dahomey | Brownsville | 1 | P | 244 | 10 | 6 | NA | NA | NA | NA | 0 | 30 | 0.0000000 |
| 1125 | 4 | 1 | 563 | F | Dahomey | Dahomey | 1 | P | 253 | 10 | 15 | 1.062 | 19 | 24 | 43 | NA | NA | NA |
| 1126 | 4 | 1 | 563 | M | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1127 | 4 | 1 | 564 | F | Israel | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1128 | 4 | 1 | 564 | M | Dahomey | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1129 | 4 | 1 | 565 | F | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1130 | 4 | 1 | 565 | M | Dahomey | Sweden | 1 | P | 290 | 12 | 4 | NA | NA | NA | NA | 0 | 41 | 0.0000000 |
| 1131 | 4 | 1 | 566 | F | Barcelona | Israel | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1132 | 4 | 1 | 566 | M | Israel | Barcelona | 1 | N | NA | NA | NA | 0.903 | NA | NA | NA | 0 | 80 | 0.0000000 |
| 1133 | 4 | 1 | 567 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1134 | 4 | 1 | 567 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1135 | 4 | 1 | 568 | F | Dahomey | Israel | 1 | L | 245 | 10 | 7 | 1.121 | 44 | 35 | 79 | NA | NA | NA |
| 1136 | 4 | 1 | 568 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1137 | 4 | 1 | 569 | F | Israel | Israel | 1 | N | 268 | 11 | 6 | 0.978 | 0 | 0 | 0 | NA | NA | NA |
| 1138 | 4 | 1 | 569 | M | Israel | Israel | 1 | N | 265 | 11 | 3 | 0.880 | NA | NA | NA | 0 | 84 | 0.0000000 |
| 1139 | 4 | 1 | 570 | F | Sweden | Israel | 1 | N | 264 | 11 | 2 | 0.975 | 14 | 21 | 35 | NA | NA | NA |
| 1140 | 4 | 1 | 570 | M | Israel | Sweden | 1 | N | 252 | 10 | 14 | 0.933 | NA | NA | NA | 21 | 61 | 0.2560976 |
| 1141 | 4 | 1 | 571 | F | Barcelona | Sweden | 1 | N | 267 | 11 | 5 | 1.044 | 35 | 34 | 69 | NA | NA | NA |
| 1142 | 4 | 1 | 571 | M | Sweden | Barcelona | 1 | N | 247 | 10 | 9 | 1.002 | NA | NA | NA | 125 | 0 | 1.0000000 |
| 1143 | 4 | 1 | 572 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1144 | 4 | 1 | 572 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1145 | 4 | 1 | 573 | F | Dahomey | Sweden | 1 | N | 249 | 10 | 11 | 0.895 | 0 | 0 | 0 | NA | NA | NA |
| 1146 | 4 | 1 | 573 | M | Sweden | Dahomey | 1 | N | 247 | 10 | 9 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1147 | 4 | 1 | 574 | F | Israel | Sweden | 1 | P | 248 | 10 | 10 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1148 | 4 | 1 | 574 | M | Sweden | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1149 | 4 | 1 | 575 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1150 | 4 | 1 | 575 | M | Sweden | Sweden | 1 | P | 250 | 10 | 12 | 0.913 | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1151 | 4 | 1 | 576 | F | Barcelona | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1152 | 4 | 1 | 576 | M | Barcelona | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1153 | 4 | 1 | 577 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1154 | 4 | 1 | 577 | M | Barcelona | Brownsville | 1 | L | NA | NA | NA | 1.159 | NA | NA | NA | 0 | 58 | 0.0000000 |
| 1155 | 4 | 1 | 578 | F | Dahomey | Barcelona | 1 | P | 270 | 11 | 8 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1156 | 4 | 1 | 578 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1157 | 4 | 1 | 579 | F | Israel | Barcelona | 1 | P | NA | NA | NA | 1.042 | 21 | 14 | 35 | NA | NA | NA |
| 1158 | 4 | 1 | 579 | M | Barcelona | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1159 | 4 | 1 | 580 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1160 | 4 | 1 | 580 | M | Barcelona | Sweden | 1 | L | 299 | 12 | 13 | NA | NA | NA | NA | NA | NA | NA |
| 1161 | 4 | 1 | 581 | F | Barcelona | Brownsville | 1 | P | NA | NA | NA | NA | 20 | 21 | 41 | NA | NA | NA |
| 1162 | 4 | 1 | 581 | M | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1163 | 4 | 1 | 582 | F | Brownsville | Brownsville | 1 | L | NA | NA | NA | 1.014 | 19 | 7 | 26 | NA | NA | NA |
| 1164 | 4 | 1 | 582 | M | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1171 | 4 | 1 | 586 | F | Barcelona | Dahomey | 1 | P | 245 | 10 | 7 | 1.084 | 26 | 33 | 59 | NA | NA | NA |
| 1172 | 4 | 1 | 586 | M | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1173 | 4 | 1 | 587 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1174 | 4 | 1 | 587 | M | Dahomey | Brownsville | 1 | L | NA | NA | NA | 0.995 | NA | NA | NA | 23 | 1 | 0.9583333 |
| 1175 | 4 | 1 | 588 | F | Dahomey | Dahomey | 1 | N | NA | NA | NA | 1.130 | 26 | 25 | 51 | NA | NA | NA |
| 1176 | 4 | 1 | 588 | M | Dahomey | Dahomey | 1 | N | 264 | 11 | 2 | NA | NA | NA | NA | 0 | 40 | 0.0000000 |
| 1177 | 4 | 1 | 589 | F | Israel | Dahomey | 1 | P | 250 | 10 | 12 | 1.053 | 22 | 24 | 46 | NA | NA | NA |
| 1178 | 4 | 1 | 589 | M | Dahomey | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1179 | 4 | 1 | 590 | F | Sweden | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1180 | 4 | 1 | 590 | M | Dahomey | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1181 | 4 | 1 | 591 | F | Barcelona | Israel | 1 | P | 296 | 12 | 10 | 0.909 | 0 | 0 | 0 | NA | NA | NA |
| 1182 | 4 | 1 | 591 | M | Israel | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1183 | 4 | 1 | 592 | F | Brownsville | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1184 | 4 | 1 | 592 | M | Israel | Brownsville | 1 | L | 249 | 10 | 11 | 1.007 | NA | NA | NA | 0 | 64 | 0.0000000 |
| 1185 | 4 | 1 | 593 | F | Dahomey | Israel | 1 | P | 276 | 11 | 14 | 0.992 | 17 | 17 | 34 | NA | NA | NA |
| 1186 | 4 | 1 | 593 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1187 | 4 | 1 | 594 | F | Israel | Israel | 1 | P | 252 | 10 | 14 | 0.975 | 20 | 24 | 44 | NA | NA | NA |
| 1188 | 4 | 1 | 594 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1189 | 4 | 1 | 595 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1190 | 4 | 1 | 595 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1191 | 4 | 1 | 596 | F | Barcelona | Sweden | 1 | N | 263 | 10 | 1 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1192 | 4 | 1 | 596 | M | Sweden | Barcelona | 1 | N | 263 | 10 | 1 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1193 | 4 | 1 | 597 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1194 | 4 | 1 | 597 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1195 | 4 | 1 | 598 | F | Dahomey | Sweden | 1 | N | 251 | 10 | 13 | 1.076 | 22 | 25 | 47 | NA | NA | NA |
| 1196 | 4 | 1 | 598 | M | Sweden | Dahomey | 1 | N | 268 | 11 | 6 | 0.878 | NA | NA | NA | 0 | 68 | 0.0000000 |
| 1197 | 4 | 1 | 599 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1198 | 4 | 1 | 599 | M | Sweden | Israel | 1 | P | 266 | 11 | 4 | 0.922 | NA | NA | NA | 0 | 18 | 0.0000000 |
| 1199 | 4 | 1 | 600 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1200 | 4 | 1 | 600 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1201 | 4 | 2 | 601 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1202 | 4 | 2 | 601 | M | Barcelona | Barcelona | 1 | P | 251 | 10 | 13 | 0.918 | NA | NA | NA | 75 | 42 | 0.6410256 |
| 1203 | 4 | 2 | 602 | F | Brownsville | Barcelona | 1 | N | 264 | 11 | 2 | 1.016 | 25 | 18 | 43 | NA | NA | NA |
| 1204 | 4 | 2 | 602 | M | Barcelona | Brownsville | 1 | N | 252 | 10 | 14 | NA | NA | NA | NA | 0 | 61 | 0.0000000 |
| 1205 | 4 | 2 | 603 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1206 | 4 | 2 | 603 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1207 | 4 | 2 | 604 | F | Israel | Barcelona | 1 | L | 247 | 10 | 9 | NA | 13 | 13 | 26 | NA | NA | NA |
| 1208 | 4 | 2 | 604 | M | Barcelona | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1209 | 4 | 2 | 605 | F | Sweden | Barcelona | 1 | P | NA | NA | NA | 0.904 | 16 | 16 | 32 | NA | NA | NA |
| 1210 | 4 | 2 | 605 | M | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1211 | 4 | 2 | 606 | F | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1212 | 4 | 2 | 606 | M | Brownsville | Barcelona | 1 | L | NA | NA | NA | 0.900 | NA | NA | NA | 0 | 82 | 0.0000000 |
| 1213 | 4 | 2 | 607 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1214 | 4 | 2 | 607 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1215 | 4 | 2 | 608 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1216 | 4 | 2 | 608 | M | Brownsville | Dahomey | 1 | P | 269 | 11 | 7 | 0.896 | NA | NA | NA | 0 | 84 | 0.0000000 |
| 1217 | 4 | 2 | 609 | F | Israel | Brownsville | 1 | N | 274 | 11 | 12 | NA | 27 | 23 | 50 | NA | NA | NA |
| 1218 | 4 | 2 | 609 | M | Brownsville | Israel | 1 | N | 265 | 11 | 3 | 0.931 | NA | NA | NA | 0 | 61 | 0.0000000 |
| 1219 | 4 | 2 | 610 | F | Sweden | Brownsville | 1 | P | NA | NA | NA | 1.073 | 0 | 0 | 0 | NA | NA | NA |
| 1220 | 4 | 2 | 610 | M | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1221 | 4 | 2 | 611 | F | Barcelona | Dahomey | 1 | L | 252 | 10 | 14 | 1.014 | 0 | 0 | 0 | NA | NA | NA |
| 1222 | 4 | 2 | 611 | M | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1223 | 4 | 2 | 612 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1224 | 4 | 2 | 612 | M | Dahomey | Brownsville | 1 | L | 246 | 10 | 8 | 1.004 | NA | NA | NA | 0 | 89 | 0.0000000 |
| 1225 | 4 | 2 | 613 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1226 | 4 | 2 | 613 | M | Dahomey | Dahomey | 1 | P | 244 | 10 | 6 | 1.037 | NA | NA | NA | 104 | 31 | 0.7703704 |
| 1227 | 4 | 2 | 614 | F | Israel | Dahomey | 1 | L | 246 | 10 | 8 | 1.060 | 23 | 15 | 38 | NA | NA | NA |
| 1228 | 4 | 2 | 614 | M | Dahomey | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1229 | 4 | 2 | 615 | F | Sweden | Dahomey | 1 | L | 269 | 11 | 7 | 1.042 | 29 | 29 | 58 | NA | NA | NA |
| 1230 | 4 | 2 | 615 | M | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1231 | 4 | 2 | 616 | F | Barcelona | Israel | 1 | N | 247 | 10 | 9 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1232 | 4 | 2 | 616 | M | Israel | Barcelona | 1 | N | 244 | 10 | 6 | 1.007 | NA | NA | NA | 0 | 68 | 0.0000000 |
| 1233 | 4 | 2 | 617 | F | Brownsville | Israel | 1 | P | 245 | 10 | 7 | 1.045 | 20 | 25 | 45 | NA | NA | NA |
| 1234 | 4 | 2 | 617 | M | Israel | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1235 | 4 | 2 | 618 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1236 | 4 | 2 | 618 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1237 | 4 | 2 | 619 | F | Israel | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1238 | 4 | 2 | 619 | M | Israel | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1239 | 4 | 2 | 620 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1240 | 4 | 2 | 620 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1243 | 4 | 2 | 622 | F | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1244 | 4 | 2 | 622 | M | Sweden | Brownsville | 1 | L | 245 | 10 | 7 | 1.080 | NA | NA | NA | 149 | 0 | 1.0000000 |
| 1245 | 4 | 2 | 623 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1246 | 4 | 2 | 623 | M | Sweden | Dahomey | 1 | P | 244 | 10 | 6 | 1.021 | NA | NA | NA | 125 | 0 | 1.0000000 |
| 1247 | 4 | 2 | 624 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1248 | 4 | 2 | 624 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1249 | 4 | 2 | 625 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1250 | 4 | 2 | 625 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1251 | 4 | 2 | 626 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1252 | 4 | 2 | 626 | M | Barcelona | Barcelona | 1 | L | 247 | 10 | 9 | 1.073 | NA | NA | NA | 161 | 1 | 0.9938272 |
| 1253 | 4 | 2 | 627 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1254 | 4 | 2 | 627 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1255 | 4 | 2 | 628 | F | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1256 | 4 | 2 | 628 | M | Barcelona | Dahomey | 1 | P | 264 | 11 | 2 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1257 | 4 | 2 | 629 | F | Israel | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1258 | 4 | 2 | 629 | M | Barcelona | Israel | 1 | L | 248 | 10 | 10 | 1.031 | NA | NA | NA | 0 | 30 | 0.0000000 |
| 1259 | 4 | 2 | 630 | F | Sweden | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1260 | 4 | 2 | 630 | M | Barcelona | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1261 | 4 | 2 | 631 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1262 | 4 | 2 | 631 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1263 | 4 | 2 | 632 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1264 | 4 | 2 | 632 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1265 | 4 | 2 | 633 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1266 | 4 | 2 | 633 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1267 | 4 | 2 | 634 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1268 | 4 | 2 | 634 | M | Brownsville | Israel | 1 | L | 248 | 10 | 10 | NA | NA | NA | NA | 0 | 5 | 0.0000000 |
| 1269 | 4 | 2 | 635 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1270 | 4 | 2 | 635 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1271 | 4 | 2 | 636 | F | Barcelona | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1272 | 4 | 2 | 636 | M | Dahomey | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1273 | 4 | 2 | 637 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1274 | 4 | 2 | 637 | M | Dahomey | Brownsville | 1 | P | NA | NA | NA | 0.878 | NA | NA | NA | 0 | 83 | 0.0000000 |
| 1275 | 4 | 2 | 638 | F | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1276 | 4 | 2 | 638 | M | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1277 | 4 | 2 | 639 | F | Israel | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1278 | 4 | 2 | 639 | M | Dahomey | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1279 | 4 | 2 | 640 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1280 | 4 | 2 | 640 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1281 | 4 | 2 | 641 | F | Barcelona | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1282 | 4 | 2 | 641 | M | Israel | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1283 | 4 | 2 | 642 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1284 | 4 | 2 | 642 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1285 | 4 | 2 | 643 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1286 | 4 | 2 | 643 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1287 | 4 | 2 | 644 | F | Israel | Israel | 1 | N | NA | NA | NA | 1.045 | 34 | 24 | 58 | NA | NA | NA |
| 1288 | 4 | 2 | 644 | M | Israel | Israel | 1 | N | 246 | 10 | 8 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1289 | 4 | 2 | 645 | F | Sweden | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1290 | 4 | 2 | 645 | M | Israel | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1291 | 4 | 2 | 646 | F | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1292 | 4 | 2 | 646 | M | Sweden | Barcelona | 1 | L | 266 | 11 | 4 | 1.047 | NA | NA | NA | 75 | 7 | 0.9146341 |
| 1295 | 4 | 2 | 648 | F | Dahomey | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1296 | 4 | 2 | 648 | M | Sweden | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1297 | 4 | 2 | 649 | F | Israel | Sweden | 1 | L | 249 | 10 | 11 | 1.024 | 23 | 25 | 48 | NA | NA | NA |
| 1298 | 4 | 2 | 649 | M | Sweden | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1299 | 4 | 2 | 650 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1300 | 4 | 2 | 650 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1301 | 4 | 2 | 651 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1302 | 4 | 2 | 651 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1303 | 4 | 2 | 652 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1304 | 4 | 2 | 652 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1305 | 4 | 2 | 653 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1306 | 4 | 2 | 653 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1307 | 4 | 2 | 654 | F | Israel | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1308 | 4 | 2 | 654 | M | Barcelona | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1309 | 4 | 2 | 655 | F | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1310 | 4 | 2 | 655 | M | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1311 | 4 | 2 | 656 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1312 | 4 | 2 | 656 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1313 | 4 | 2 | 657 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1314 | 4 | 2 | 657 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1315 | 4 | 2 | 658 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1316 | 4 | 2 | 658 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1317 | 4 | 2 | 659 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1318 | 4 | 2 | 659 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1319 | 4 | 2 | 660 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1320 | 4 | 2 | 660 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1321 | 4 | 2 | 661 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1322 | 4 | 2 | 661 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1323 | 4 | 2 | 662 | F | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1324 | 4 | 2 | 662 | M | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1325 | 4 | 2 | 663 | F | Dahomey | Dahomey | 1 | P | 263 | 10 | 1 | 0.967 | 20 | 21 | 41 | NA | NA | NA |
| 1326 | 4 | 2 | 663 | M | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1327 | 4 | 2 | 664 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1328 | 4 | 2 | 664 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1329 | 4 | 2 | 665 | F | Sweden | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1330 | 4 | 2 | 665 | M | Dahomey | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1331 | 4 | 2 | 666 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1332 | 4 | 2 | 666 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1333 | 4 | 2 | 667 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1334 | 4 | 2 | 667 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1335 | 4 | 2 | 668 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1336 | 4 | 2 | 668 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1337 | 4 | 2 | 669 | F | Israel | Israel | 1 | P | 250 | 10 | 12 | 1.038 | 24 | 16 | 40 | NA | NA | NA |
| 1338 | 4 | 2 | 669 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1339 | 4 | 2 | 670 | F | Sweden | Israel | 1 | L | 268 | 11 | 6 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1340 | 4 | 2 | 670 | M | Israel | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1341 | 4 | 2 | 671 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1342 | 4 | 2 | 671 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1343 | 4 | 2 | 672 | F | Brownsville | Sweden | 1 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1344 | 4 | 2 | 672 | M | Sweden | Brownsville | 1 | N | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 1345 | 4 | 2 | 673 | F | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1346 | 4 | 2 | 673 | M | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1347 | 4 | 2 | 674 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1348 | 4 | 2 | 674 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1349 | 4 | 2 | 675 | F | Sweden | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1350 | 4 | 2 | 675 | M | Sweden | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1351 | 4 | 2 | 676 | F | Barcelona | Barcelona | 1 | L | 250 | 10 | 12 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1352 | 4 | 2 | 676 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1353 | 4 | 2 | 677 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1354 | 4 | 2 | 677 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1355 | 4 | 2 | 678 | F | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1356 | 4 | 2 | 678 | M | Barcelona | Dahomey | 1 | P | 250 | 10 | 12 | 1.077 | NA | NA | NA | 103 | 0 | 1.0000000 |
| 1357 | 4 | 2 | 679 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1358 | 4 | 2 | 679 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1359 | 4 | 2 | 680 | F | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1360 | 4 | 2 | 680 | M | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1361 | 4 | 2 | 681 | F | Barcelona | Brownsville | 1 | L | 264 | 11 | 2 | 0.963 | 11 | 6 | 17 | NA | NA | NA |
| 1362 | 4 | 2 | 681 | M | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1363 | 4 | 2 | 682 | F | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1364 | 4 | 2 | 682 | M | Brownsville | Brownsville | 1 | L | 265 | 11 | 3 | 0.841 | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1365 | 4 | 2 | 683 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1366 | 4 | 2 | 683 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1367 | 4 | 2 | 684 | F | Israel | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1368 | 4 | 2 | 684 | M | Brownsville | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1369 | 4 | 2 | 685 | F | Sweden | Brownsville | 1 | L | NA | NA | NA | 1.005 | 4 | 3 | 7 | NA | NA | NA |
| 1370 | 4 | 2 | 685 | M | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1371 | 4 | 2 | 686 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1372 | 4 | 2 | 686 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1373 | 4 | 2 | 687 | F | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1374 | 4 | 2 | 687 | M | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1375 | 4 | 2 | 688 | F | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1376 | 4 | 2 | 688 | M | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1377 | 4 | 2 | 689 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1378 | 4 | 2 | 689 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1381 | 4 | 2 | 691 | F | Barcelona | Israel | 1 | N | 275 | 11 | 13 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1382 | 4 | 2 | 691 | M | Israel | Barcelona | 1 | N | 251 | 10 | 13 | 1.061 | NA | NA | NA | 33 | 0 | 1.0000000 |
| 1383 | 4 | 2 | 692 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1384 | 4 | 2 | 692 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1385 | 4 | 2 | 693 | F | Dahomey | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1386 | 4 | 2 | 693 | M | Israel | Dahomey | 1 | L | NA | NA | NA | 0.957 | NA | NA | NA | 146 | 1 | 0.9931973 |
| 1387 | 4 | 2 | 694 | F | Israel | Israel | 1 | L | 248 | 10 | 10 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1388 | 4 | 2 | 694 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1389 | 4 | 2 | 695 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1390 | 4 | 2 | 695 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1391 | 4 | 2 | 696 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1392 | 4 | 2 | 696 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1393 | 4 | 2 | 697 | F | Brownsville | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1394 | 4 | 2 | 697 | M | Sweden | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1395 | 4 | 2 | 698 | F | Dahomey | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1396 | 4 | 2 | 698 | M | Sweden | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1397 | 4 | 2 | 699 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1398 | 4 | 2 | 699 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1399 | 4 | 2 | 700 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1400 | 4 | 2 | 700 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1401 | 5 | 1 | 701 | F | Barcelona | Barcelona | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1402 | 5 | 1 | 701 | M | Barcelona | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1403 | 5 | 1 | 702 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1404 | 5 | 1 | 702 | M | Barcelona | Brownsville | 1 | L | 286 | 12 | 0 | 0.751 | NA | NA | NA | 0 | 46 | 0.0000000 |
| 1405 | 5 | 1 | 703 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1406 | 5 | 1 | 703 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1407 | 5 | 1 | 704 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1408 | 5 | 1 | 704 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1409 | 5 | 1 | 705 | F | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1410 | 5 | 1 | 705 | M | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1411 | 5 | 1 | 706 | F | Barcelona | Brownsville | 1 | L | 267 | 11 | 5 | NA | NA | NA | NA | NA | NA | NA |
| 1412 | 5 | 1 | 706 | M | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1413 | 5 | 1 | 707 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1414 | 5 | 1 | 707 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1415 | 5 | 1 | 708 | F | Dahomey | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1416 | 5 | 1 | 708 | M | Brownsville | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1417 | 5 | 1 | 709 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1418 | 5 | 1 | 709 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1419 | 5 | 1 | 710 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1420 | 5 | 1 | 710 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1421 | 5 | 1 | 711 | F | Barcelona | Dahomey | 1 | P | 280 | 11 | 18 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1422 | 5 | 1 | 711 | M | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1423 | 5 | 1 | 712 | F | Brownsville | Dahomey | 1 | P | 284 | 11 | 22 | NA | 1 | 0 | 1 | NA | NA | NA |
| 1424 | 5 | 1 | 712 | M | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1425 | 5 | 1 | 713 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1426 | 5 | 1 | 713 | M | Dahomey | Dahomey | 1 | L | 237 | 9 | 23 | 0.963 | NA | NA | NA | 0 | 14 | 0.0000000 |
| 1427 | 5 | 1 | 714 | F | Israel | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1428 | 5 | 1 | 714 | M | Dahomey | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1429 | 5 | 1 | 715 | F | Sweden | Dahomey | 1 | L | 268 | 11 | 6 | 1.071 | 25 | 20 | 45 | NA | NA | NA |
| 1430 | 5 | 1 | 715 | M | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1431 | 5 | 1 | 716 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1432 | 5 | 1 | 716 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1433 | 5 | 1 | 717 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1434 | 5 | 1 | 717 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1435 | 5 | 1 | 718 | F | Dahomey | Israel | 1 | L | 257 | 10 | 19 | 1.016 | 24 | 30 | 54 | NA | NA | NA |
| 1436 | 5 | 1 | 718 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1437 | 5 | 1 | 719 | F | Israel | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1438 | 5 | 1 | 719 | M | Israel | Israel | 1 | L | 278 | 11 | 16 | 0.862 | NA | NA | NA | 0 | 47 | 0.0000000 |
| 1439 | 5 | 1 | 720 | F | Sweden | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1440 | 5 | 1 | 720 | M | Israel | Sweden | 1 | L | 263 | 10 | 1 | 1.011 | NA | NA | NA | 0 | 27 | 0.0000000 |
| 1441 | 5 | 1 | 721 | F | Barcelona | Sweden | 1 | P | 281 | 11 | 19 | 0.901 | 5 | 5 | 10 | NA | NA | NA |
| 1442 | 5 | 1 | 721 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1443 | 5 | 1 | 722 | F | Brownsville | Sweden | 1 | N | 283 | 11 | 21 | 0.918 | 17 | 16 | 33 | NA | NA | NA |
| 1444 | 5 | 1 | 722 | M | Sweden | Brownsville | 1 | N | 278 | 11 | 16 | 0.890 | NA | NA | NA | 0 | 27 | 0.0000000 |
| 1445 | 5 | 1 | 723 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1446 | 5 | 1 | 723 | M | Sweden | Dahomey | 1 | L | 270 | 11 | 8 | 1.036 | NA | NA | NA | 23 | 9 | 0.7187500 |
| 1447 | 5 | 1 | 724 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1448 | 5 | 1 | 724 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1449 | 5 | 1 | 725 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1450 | 5 | 1 | 725 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1451 | 5 | 1 | 726 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1452 | 5 | 1 | 726 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1453 | 5 | 1 | 727 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1454 | 5 | 1 | 727 | M | Barcelona | Brownsville | 1 | L | 258 | 10 | 20 | 1.038 | NA | NA | NA | 0 | 65 | 0.0000000 |
| 1455 | 5 | 1 | 728 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1456 | 5 | 1 | 728 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1457 | 5 | 1 | 729 | F | Israel | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1458 | 5 | 1 | 729 | M | Barcelona | Israel | 1 | L | 264 | 11 | 2 | 0.998 | NA | NA | NA | 0 | 18 | 0.0000000 |
| 1459 | 5 | 1 | 730 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1460 | 5 | 1 | 730 | M | Barcelona | Sweden | 1 | L | 267 | 11 | 5 | NA | NA | NA | NA | 0 | 20 | 0.0000000 |
| 1463 | 5 | 1 | 732 | F | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1464 | 5 | 1 | 732 | M | Brownsville | Brownsville | 1 | P | 279 | 11 | 17 | 0.907 | NA | NA | NA | 0 | 56 | 0.0000000 |
| 1465 | 5 | 1 | 733 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1466 | 5 | 1 | 733 | M | Brownsville | Dahomey | 1 | L | 272 | 11 | 10 | 0.944 | NA | NA | NA | 0 | 12 | 0.0000000 |
| 1467 | 5 | 1 | 734 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1468 | 5 | 1 | 734 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1469 | 5 | 1 | 735 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1470 | 5 | 1 | 735 | M | Brownsville | Sweden | 1 | L | 243 | 10 | 5 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1471 | 5 | 1 | 736 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1472 | 5 | 1 | 736 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1473 | 5 | 1 | 737 | F | Brownsville | Dahomey | 1 | N | 280 | 11 | 18 | NA | 1 | 1 | 2 | NA | NA | NA |
| 1474 | 5 | 1 | 737 | M | Dahomey | Brownsville | 1 | N | 287 | 12 | 1 | NA | NA | NA | NA | 0 | 86 | 0.0000000 |
| 1475 | 5 | 1 | 738 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1476 | 5 | 1 | 738 | M | Dahomey | Dahomey | 1 | P | 249 | 10 | 11 | 1.007 | NA | NA | NA | 0 | 15 | 0.0000000 |
| 1477 | 5 | 1 | 739 | F | Israel | Dahomey | 1 | L | 251 | 10 | 13 | 1.113 | 34 | 30 | 64 | NA | NA | NA |
| 1478 | 5 | 1 | 739 | M | Dahomey | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1479 | 5 | 1 | 740 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1480 | 5 | 1 | 740 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1481 | 5 | 1 | 741 | F | Barcelona | Israel | 1 | L | 264 | 11 | 2 | 0.979 | 16 | 18 | 34 | NA | NA | NA |
| 1482 | 5 | 1 | 741 | M | Israel | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1483 | 5 | 1 | 742 | F | Brownsville | Israel | 1 | L | 279 | 11 | 17 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1484 | 5 | 1 | 742 | M | Israel | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1487 | 5 | 1 | 744 | F | Israel | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1488 | 5 | 1 | 744 | M | Israel | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1489 | 5 | 1 | 745 | F | Sweden | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1490 | 5 | 1 | 745 | M | Israel | Sweden | 1 | L | 245 | 10 | 7 | 1.140 | NA | NA | NA | 120 | 8 | 0.9375000 |
| 1491 | 5 | 1 | 746 | F | Barcelona | Sweden | 1 | L | 267 | 11 | 5 | 1.045 | 17 | 21 | 38 | NA | NA | NA |
| 1492 | 5 | 1 | 746 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1493 | 5 | 1 | 747 | F | Brownsville | Sweden | 1 | L | 239 | 9 | 1 | 1.143 | 19 | 28 | 47 | NA | NA | NA |
| 1494 | 5 | 1 | 747 | M | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1495 | 5 | 1 | 748 | F | Dahomey | Sweden | 1 | N | 282 | 11 | 20 | 0.976 | 5 | 9 | 14 | NA | NA | NA |
| 1496 | 5 | 1 | 748 | M | Sweden | Dahomey | 1 | N | 252 | 10 | 14 | 1.047 | NA | NA | NA | 21 | 7 | 0.7500000 |
| 1497 | 5 | 1 | 749 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1498 | 5 | 1 | 749 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1499 | 5 | 1 | 750 | F | Sweden | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1500 | 5 | 1 | 750 | M | Sweden | Sweden | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1501 | 5 | 2 | 751 | F | Barcelona | Barcelona | 1 | L | 240 | 10 | 2 | 1.053 | 10 | 18 | 28 | NA | NA | NA |
| 1502 | 5 | 2 | 751 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1503 | 5 | 2 | 752 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1504 | 5 | 2 | 752 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1505 | 5 | 2 | 753 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1506 | 5 | 2 | 753 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1507 | 5 | 2 | 754 | F | Israel | Barcelona | 1 | L | 260 | 10 | 22 | NA | 28 | 24 | 52 | NA | NA | NA |
| 1508 | 5 | 2 | 754 | M | Barcelona | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1509 | 5 | 2 | 755 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1510 | 5 | 2 | 755 | M | Barcelona | Sweden | 1 | L | 250 | 10 | 12 | 1.024 | NA | NA | NA | 10 | 0 | 1.0000000 |
| 1511 | 5 | 2 | 756 | F | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1512 | 5 | 2 | 756 | M | Brownsville | Barcelona | 1 | L | 257 | 10 | 19 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1513 | 5 | 2 | 757 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1514 | 5 | 2 | 757 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1515 | 5 | 2 | 758 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1516 | 5 | 2 | 758 | M | Brownsville | Dahomey | 1 | L | 259 | 10 | 21 | 1.084 | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1517 | 5 | 2 | 759 | F | Israel | Brownsville | 1 | L | 259 | 10 | 21 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1518 | 5 | 2 | 759 | M | Brownsville | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1519 | 5 | 2 | 760 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1520 | 5 | 2 | 760 | M | Brownsville | Sweden | 1 | L | 259 | 10 | 21 | 1.042 | NA | NA | NA | 0 | 88 | 0.0000000 |
| 1521 | 5 | 2 | 761 | F | Barcelona | Dahomey | 1 | P | 288 | 12 | 2 | 0.869 | 0 | 0 | 0 | NA | NA | NA |
| 1522 | 5 | 2 | 761 | M | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1523 | 5 | 2 | 762 | F | Brownsville | Dahomey | 1 | L | 267 | 11 | 5 | 1.209 | 24 | 38 | 62 | NA | NA | NA |
| 1524 | 5 | 2 | 762 | M | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1525 | 5 | 2 | 763 | F | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1526 | 5 | 2 | 763 | M | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1527 | 5 | 2 | 764 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1528 | 5 | 2 | 764 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1529 | 5 | 2 | 765 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1530 | 5 | 2 | 765 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1531 | 5 | 2 | 766 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1532 | 5 | 2 | 766 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1533 | 5 | 2 | 767 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1534 | 5 | 2 | 767 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1535 | 5 | 2 | 768 | F | Dahomey | Israel | 1 | L | 245 | 10 | 7 | 1.178 | 37 | 29 | 66 | NA | NA | NA |
| 1536 | 5 | 2 | 768 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1537 | 5 | 2 | 769 | F | Israel | Israel | 1 | L | 247 | 10 | 9 | 1.221 | 38 | 25 | 63 | NA | NA | NA |
| 1538 | 5 | 2 | 769 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1539 | 5 | 2 | 770 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1540 | 5 | 2 | 770 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1541 | 5 | 2 | 771 | F | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1542 | 5 | 2 | 771 | M | Sweden | Barcelona | 1 | L | 242 | 10 | 4 | 1.040 | NA | NA | NA | 12 | 64 | 0.1578947 |
| 1543 | 5 | 2 | 772 | F | Brownsville | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1544 | 5 | 2 | 772 | M | Sweden | Brownsville | 1 | L | 232 | 9 | 18 | NA | NA | NA | NA | 50 | 6 | 0.8928571 |
| 1547 | 5 | 2 | 774 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1548 | 5 | 2 | 774 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1549 | 5 | 2 | 775 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1550 | 5 | 2 | 775 | M | Sweden | Sweden | 1 | L | 262 | 10 | 0 | 0.971 | NA | NA | NA | 0 | 12 | 0.0000000 |
| 1551 | 5 | 2 | 776 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1552 | 5 | 2 | 776 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1553 | 5 | 2 | 777 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1554 | 5 | 2 | 777 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1555 | 5 | 2 | 778 | F | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1556 | 5 | 2 | 778 | M | Barcelona | Dahomey | 1 | L | 263 | 10 | 1 | 0.978 | NA | NA | NA | 116 | 37 | 0.7581699 |
| 1557 | 5 | 2 | 779 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1558 | 5 | 2 | 779 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1559 | 5 | 2 | 780 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1560 | 5 | 2 | 780 | M | Barcelona | Sweden | 1 | L | 270 | 11 | 8 | 1.011 | NA | NA | NA | 16 | 7 | 0.6956522 |
| 1561 | 5 | 2 | 781 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1562 | 5 | 2 | 781 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1563 | 5 | 2 | 782 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1564 | 5 | 2 | 782 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1565 | 5 | 2 | 783 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1566 | 5 | 2 | 783 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1567 | 5 | 2 | 784 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1568 | 5 | 2 | 784 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1569 | 5 | 2 | 785 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1570 | 5 | 2 | 785 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1573 | 5 | 2 | 787 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1574 | 5 | 2 | 787 | M | Dahomey | Brownsville | 1 | P | 275 | 11 | 13 | 0.823 | NA | NA | NA | 0 | 79 | 0.0000000 |
| 1575 | 5 | 2 | 788 | F | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1576 | 5 | 2 | 788 | M | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1577 | 5 | 2 | 789 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1578 | 5 | 2 | 789 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1579 | 5 | 2 | 790 | F | Sweden | Dahomey | 1 | N | 253 | 10 | 15 | 0.964 | 2 | 6 | 8 | NA | NA | NA |
| 1580 | 5 | 2 | 790 | M | Dahomey | Sweden | 1 | N | 273 | 11 | 11 | 0.902 | NA | NA | NA | 0 | 63 | 0.0000000 |
| 1581 | 5 | 2 | 791 | F | Barcelona | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1582 | 5 | 2 | 791 | M | Israel | Barcelona | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1583 | 5 | 2 | 792 | F | Brownsville | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1584 | 5 | 2 | 792 | M | Israel | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1585 | 5 | 2 | 793 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1586 | 5 | 2 | 793 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1587 | 5 | 2 | 794 | F | Israel | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1588 | 5 | 2 | 794 | M | Israel | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1589 | 5 | 2 | 795 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1590 | 5 | 2 | 795 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1591 | 5 | 2 | 796 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1592 | 5 | 2 | 796 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1595 | 5 | 2 | 798 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1596 | 5 | 2 | 798 | M | Sweden | Dahomey | 1 | L | 246 | 10 | 8 | NA | NA | NA | NA | 69 | 0 | 1.0000000 |
| 1597 | 5 | 2 | 799 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1598 | 5 | 2 | 799 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1599 | 5 | 2 | 800 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1600 | 5 | 2 | 800 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1601 | 5 | 1 | 801 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1602 | 5 | 1 | 801 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1603 | 5 | 1 | 802 | F | Brownsville | Barcelona | 1 | L | 280 | 11 | 18 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1604 | 5 | 1 | 802 | M | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1605 | 5 | 1 | 803 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1606 | 5 | 1 | 803 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1607 | 5 | 1 | 804 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1608 | 5 | 1 | 804 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1609 | 5 | 1 | 805 | F | Sweden | Barcelona | 1 | L | 286 | 12 | 0 | 0.847 | 15 | 14 | 29 | NA | NA | NA |
| 1610 | 5 | 1 | 805 | M | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1611 | 5 | 1 | 806 | F | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1612 | 5 | 1 | 806 | M | Brownsville | Barcelona | 1 | L | 268 | 11 | 6 | 0.905 | NA | NA | NA | 0 | 11 | 0.0000000 |
| 1613 | 5 | 1 | 807 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1614 | 5 | 1 | 807 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1615 | 5 | 1 | 808 | F | Dahomey | Brownsville | 1 | L | 241 | 10 | 3 | 1.187 | 28 | 21 | 49 | NA | NA | NA |
| 1616 | 5 | 1 | 808 | M | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1617 | 5 | 1 | 809 | F | Israel | Brownsville | 1 | L | 272 | 11 | 10 | 0.926 | 16 | 22 | 38 | NA | NA | NA |
| 1618 | 5 | 1 | 809 | M | Brownsville | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1619 | 5 | 1 | 810 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1620 | 5 | 1 | 810 | M | Brownsville | Sweden | 1 | L | 260 | 10 | 22 | 1.010 | NA | NA | NA | 0 | 41 | 0.0000000 |
| 1621 | 5 | 1 | 811 | F | Barcelona | Dahomey | 1 | N | 263 | 10 | 1 | 0.979 | 20 | 20 | 40 | NA | NA | NA |
| 1622 | 5 | 1 | 811 | M | Dahomey | Barcelona | 1 | N | 259 | 10 | 21 | 0.988 | NA | NA | NA | 174 | 0 | 1.0000000 |
| 1623 | 5 | 1 | 812 | F | Brownsville | Dahomey | 1 | P | 246 | 10 | 8 | 1.078 | 14 | 14 | 28 | NA | NA | NA |
| 1624 | 5 | 1 | 812 | M | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1625 | 5 | 1 | 813 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1626 | 5 | 1 | 813 | M | Dahomey | Dahomey | 1 | L | 246 | 10 | 8 | 0.989 | NA | NA | NA | 56 | 0 | 1.0000000 |
| 1627 | 5 | 1 | 814 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1628 | 5 | 1 | 814 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1629 | 5 | 1 | 815 | F | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1630 | 5 | 1 | 815 | M | Dahomey | Sweden | 1 | L | 246 | 10 | 8 | 0.976 | NA | NA | NA | 116 | 9 | 0.9280000 |
| 1631 | 5 | 1 | 816 | F | Barcelona | Israel | 1 | L | 253 | 10 | 15 | 1.068 | 20 | 26 | 46 | NA | NA | NA |
| 1632 | 5 | 1 | 816 | M | Israel | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1633 | 5 | 1 | 817 | F | Brownsville | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1634 | 5 | 1 | 817 | M | Israel | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1635 | 5 | 1 | 818 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1636 | 5 | 1 | 818 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1637 | 5 | 1 | 819 | F | Israel | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1638 | 5 | 1 | 819 | M | Israel | Israel | 1 | P | 280 | 11 | 18 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1639 | 5 | 1 | 820 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1640 | 5 | 1 | 820 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1641 | 5 | 1 | 821 | F | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1642 | 5 | 1 | 821 | M | Sweden | Barcelona | 1 | L | 274 | 11 | 12 | 0.912 | NA | NA | NA | 9 | 0 | 1.0000000 |
| 1643 | 5 | 1 | 822 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1644 | 5 | 1 | 822 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1645 | 5 | 1 | 823 | F | Dahomey | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1646 | 5 | 1 | 823 | M | Sweden | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1647 | 5 | 1 | 824 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1648 | 5 | 1 | 824 | M | Sweden | Israel | 1 | P | 263 | 10 | 1 | 0.939 | NA | NA | NA | 54 | 62 | 0.4655172 |
| 1649 | 5 | 1 | 825 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1650 | 5 | 1 | 825 | M | Sweden | Sweden | 1 | L | 270 | 11 | 8 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1651 | 5 | 1 | 826 | F | Barcelona | Barcelona | 1 | L | 244 | 10 | 6 | 1.190 | 36 | 23 | 59 | NA | NA | NA |
| 1652 | 5 | 1 | 826 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1653 | 5 | 1 | 827 | F | Brownsville | Barcelona | 1 | P | 280 | 11 | 18 | 1.027 | 17 | 23 | 40 | NA | NA | NA |
| 1654 | 5 | 1 | 827 | M | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1655 | 5 | 1 | 828 | F | Dahomey | Barcelona | 1 | N | 259 | 10 | 21 | 1.054 | 27 | 23 | 50 | NA | NA | NA |
| 1656 | 5 | 1 | 828 | M | Barcelona | Dahomey | 1 | N | NA | NA | NA | 0.983 | NA | NA | NA | 15 | 83 | 0.1530612 |
| 1657 | 5 | 1 | 829 | F | Israel | Barcelona | 1 | P | 252 | 10 | 14 | 1.089 | 28 | 36 | 64 | NA | NA | NA |
| 1658 | 5 | 1 | 829 | M | Barcelona | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1659 | 5 | 1 | 830 | F | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1660 | 5 | 1 | 830 | M | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1661 | 5 | 1 | 831 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1662 | 5 | 1 | 831 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1663 | 5 | 1 | 832 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1664 | 5 | 1 | 832 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1665 | 5 | 1 | 833 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1666 | 5 | 1 | 833 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1667 | 5 | 1 | 834 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1668 | 5 | 1 | 834 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1669 | 5 | 1 | 835 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1670 | 5 | 1 | 835 | M | Brownsville | Sweden | 1 | P | 261 | 10 | 23 | 0.945 | NA | NA | NA | 0 | 89 | 0.0000000 |
| 1671 | 5 | 1 | 836 | F | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1672 | 5 | 1 | 836 | M | Dahomey | Barcelona | 1 | P | 249 | 10 | 11 | 0.984 | NA | NA | NA | 0 | 35 | 0.0000000 |
| 1673 | 5 | 1 | 837 | F | Brownsville | Dahomey | 1 | P | 251 | 10 | 13 | 1.013 | 23 | 13 | 36 | NA | NA | NA |
| 1674 | 5 | 1 | 837 | M | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1675 | 5 | 1 | 838 | F | Dahomey | Dahomey | 1 | P | 288 | 12 | 2 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1676 | 5 | 1 | 838 | M | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1677 | 5 | 1 | 839 | F | Israel | Dahomey | 1 | L | 251 | 10 | 13 | 1.034 | 21 | 26 | 47 | NA | NA | NA |
| 1678 | 5 | 1 | 839 | M | Dahomey | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1679 | 5 | 1 | 840 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1680 | 5 | 1 | 840 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1681 | 5 | 1 | 841 | F | Barcelona | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1682 | 5 | 1 | 841 | M | Israel | Barcelona | 1 | P | 252 | 10 | 14 | 0.969 | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1683 | 5 | 1 | 842 | F | Brownsville | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1684 | 5 | 1 | 842 | M | Israel | Brownsville | 1 | L | 253 | 10 | 15 | 0.936 | NA | NA | NA | 32 | 47 | 0.4050633 |
| 1685 | 5 | 1 | 843 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1686 | 5 | 1 | 843 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1687 | 5 | 1 | 844 | F | Israel | Israel | 1 | L | 247 | 10 | 9 | 0.995 | 17 | 14 | 31 | NA | NA | NA |
| 1688 | 5 | 1 | 844 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1689 | 5 | 1 | 845 | F | Sweden | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1690 | 5 | 1 | 845 | M | Israel | Sweden | 1 | L | 270 | 11 | 8 | 0.973 | NA | NA | NA | 0 | 74 | 0.0000000 |
| 1691 | 5 | 1 | 846 | F | Barcelona | Sweden | 1 | L | 238 | 9 | 0 | 1.023 | 27 | 21 | 48 | NA | NA | NA |
| 1692 | 5 | 1 | 846 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1693 | 5 | 1 | 847 | F | Brownsville | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1694 | 5 | 1 | 847 | M | Sweden | Brownsville | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1695 | 5 | 1 | 848 | F | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1696 | 5 | 1 | 848 | M | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1697 | 5 | 1 | 849 | F | Israel | Sweden | 1 | N | 274 | 11 | 12 | 0.962 | 0 | 0 | 0 | NA | NA | NA |
| 1698 | 5 | 1 | 849 | M | Sweden | Israel | 1 | N | 270 | 11 | 8 | 0.880 | NA | NA | NA | 0 | 33 | 0.0000000 |
| 1699 | 5 | 1 | 850 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1700 | 5 | 1 | 850 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1701 | 5 | 2 | 851 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1702 | 5 | 2 | 851 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1703 | 5 | 2 | 852 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1704 | 5 | 2 | 852 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1705 | 5 | 2 | 853 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1706 | 5 | 2 | 853 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1707 | 5 | 2 | 854 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1708 | 5 | 2 | 854 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1709 | 5 | 2 | 855 | F | Sweden | Barcelona | 1 | L | 273 | 11 | 11 | 0.967 | 9 | 11 | 20 | NA | NA | NA |
| 1710 | 5 | 2 | 855 | M | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1711 | 5 | 2 | 856 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1712 | 5 | 2 | 856 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1713 | 5 | 2 | 857 | F | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1714 | 5 | 2 | 857 | M | Brownsville | Brownsville | 1 | L | 269 | 11 | 7 | 0.928 | NA | NA | NA | 0 | 101 | 0.0000000 |
| 1715 | 5 | 2 | 858 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1716 | 5 | 2 | 858 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1717 | 5 | 2 | 859 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1718 | 5 | 2 | 859 | M | Brownsville | Israel | 1 | L | 266 | 11 | 4 | 1.067 | NA | NA | NA | 0 | 52 | 0.0000000 |
| 1719 | 5 | 2 | 860 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1720 | 5 | 2 | 860 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1721 | 5 | 2 | 861 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1722 | 5 | 2 | 861 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1723 | 5 | 2 | 862 | F | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1724 | 5 | 2 | 862 | M | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1725 | 5 | 2 | 863 | F | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1726 | 5 | 2 | 863 | M | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1727 | 5 | 2 | 864 | F | Israel | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1728 | 5 | 2 | 864 | M | Dahomey | Israel | 1 | L | 271 | 11 | 9 | 0.782 | NA | NA | NA | 0 | 23 | 0.0000000 |
| 1729 | 5 | 2 | 865 | F | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1730 | 5 | 2 | 865 | M | Dahomey | Sweden | 1 | L | 281 | 11 | 19 | 1.017 | NA | NA | NA | 0 | 59 | 0.0000000 |
| 1731 | 5 | 2 | 866 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1732 | 5 | 2 | 866 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1733 | 5 | 2 | 867 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1734 | 5 | 2 | 867 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1735 | 5 | 2 | 868 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1736 | 5 | 2 | 868 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1737 | 5 | 2 | 869 | F | Israel | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1738 | 5 | 2 | 869 | M | Israel | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1739 | 5 | 2 | 870 | F | Sweden | Israel | 1 | L | 281 | 11 | 19 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1740 | 5 | 2 | 870 | M | Israel | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1741 | 5 | 2 | 871 | F | Barcelona | Sweden | 1 | L | 290 | 12 | 4 | 1.097 | 29 | 29 | 58 | NA | NA | NA |
| 1742 | 5 | 2 | 871 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1743 | 5 | 2 | 872 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1744 | 5 | 2 | 872 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1745 | 5 | 2 | 873 | F | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1746 | 5 | 2 | 873 | M | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1747 | 5 | 2 | 874 | F | Israel | Sweden | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1748 | 5 | 2 | 874 | M | Sweden | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1749 | 5 | 2 | 875 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1750 | 5 | 2 | 875 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1751 | 5 | 2 | 876 | F | Barcelona | Barcelona | 1 | L | 259 | 10 | 21 | 1.090 | 20 | 32 | 52 | NA | NA | NA |
| 1752 | 5 | 2 | 876 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1753 | 5 | 2 | 877 | F | Brownsville | Barcelona | 1 | L | 277 | 11 | 15 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1754 | 5 | 2 | 877 | M | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1755 | 5 | 2 | 878 | F | Dahomey | Barcelona | 1 | L | 250 | 10 | 12 | NA | 15 | 14 | 29 | NA | NA | NA |
| 1756 | 5 | 2 | 878 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1757 | 5 | 2 | 879 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1758 | 5 | 2 | 879 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1759 | 5 | 2 | 880 | F | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1760 | 5 | 2 | 880 | M | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1761 | 5 | 2 | 881 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1762 | 5 | 2 | 881 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1763 | 5 | 2 | 882 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1764 | 5 | 2 | 882 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1765 | 5 | 2 | 883 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1766 | 5 | 2 | 883 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1767 | 5 | 2 | 884 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1768 | 5 | 2 | 884 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1769 | 5 | 2 | 885 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1770 | 5 | 2 | 885 | M | Brownsville | Sweden | 1 | L | 285 | 11 | 23 | 0.926 | NA | NA | NA | 0 | 91 | 0.0000000 |
| 1771 | 5 | 2 | 886 | F | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1772 | 5 | 2 | 886 | M | Dahomey | Barcelona | 1 | P | 286 | 12 | 0 | 0.851 | NA | NA | NA | 0 | 18 | 0.0000000 |
| 1773 | 5 | 2 | 887 | F | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1774 | 5 | 2 | 887 | M | Dahomey | Brownsville | 1 | L | 276 | 11 | 14 | 0.821 | NA | NA | NA | 0 | 73 | 0.0000000 |
| 1775 | 5 | 2 | 888 | F | Dahomey | Dahomey | 1 | P | 272 | 11 | 10 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1776 | 5 | 2 | 888 | M | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1777 | 5 | 2 | 889 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1778 | 5 | 2 | 889 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1779 | 5 | 2 | 890 | F | Sweden | Dahomey | 1 | P | 256 | 10 | 18 | 0.977 | 13 | 23 | 36 | NA | NA | NA |
| 1780 | 5 | 2 | 890 | M | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1781 | 5 | 2 | 891 | F | Barcelona | Israel | 1 | L | 272 | 11 | 10 | 1.056 | 0 | 0 | 0 | NA | NA | NA |
| 1782 | 5 | 2 | 891 | M | Israel | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1783 | 5 | 2 | 892 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1784 | 5 | 2 | 892 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1785 | 5 | 2 | 893 | F | Dahomey | Israel | 1 | L | 245 | 10 | 7 | 1.062 | 33 | 21 | 54 | NA | NA | NA |
| 1786 | 5 | 2 | 893 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1787 | 5 | 2 | 894 | F | Israel | Israel | 1 | L | 242 | 10 | 4 | 1.198 | 0 | 0 | 0 | NA | NA | NA |
| 1788 | 5 | 2 | 894 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1789 | 5 | 2 | 895 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1790 | 5 | 2 | 895 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1791 | 5 | 2 | 896 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1792 | 5 | 2 | 896 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1793 | 5 | 2 | 897 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1794 | 5 | 2 | 897 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1795 | 5 | 2 | 898 | F | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1796 | 5 | 2 | 898 | M | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1797 | 5 | 2 | 899 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1798 | 5 | 2 | 899 | M | Sweden | Israel | 1 | L | 250 | 10 | 12 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1799 | 5 | 2 | 900 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1800 | 5 | 2 | 900 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1801 | 6 | 1 | 901 | F | Barcelona | Barcelona | 1 | L | 252 | 10 | 14 | NA | 20 | 16 | 36 | NA | NA | NA |
| 1802 | 6 | 1 | 901 | M | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1803 | 6 | 1 | 902 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1804 | 6 | 1 | 902 | M | Barcelona | Brownsville | 1 | L | 241 | 10 | 3 | 1.060 | NA | NA | NA | 36 | 68 | 0.3461538 |
| 1807 | 6 | 1 | 904 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1808 | 6 | 1 | 904 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1809 | 6 | 1 | 905 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1810 | 6 | 1 | 905 | M | Barcelona | Sweden | 1 | L | 260 | 10 | 22 | 1.084 | NA | NA | NA | 97 | 4 | 0.9603960 |
| 1811 | 6 | 1 | 906 | F | Barcelona | Brownsville | 1 | L | NA | NA | NA | 1.177 | 31 | 35 | 66 | NA | NA | NA |
| 1812 | 6 | 1 | 906 | M | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1815 | 6 | 1 | 908 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1816 | 6 | 1 | 908 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1817 | 6 | 1 | 909 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1818 | 6 | 1 | 909 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1819 | 6 | 1 | 910 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1820 | 6 | 1 | 910 | M | Brownsville | Sweden | 1 | L | 257 | 10 | 19 | 0.898 | NA | NA | NA | 0 | 34 | 0.0000000 |
| 1821 | 6 | 1 | 911 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1822 | 6 | 1 | 911 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1823 | 6 | 1 | 912 | F | Brownsville | Dahomey | 1 | N | 242 | 10 | 4 | 1.018 | 17 | 18 | 35 | NA | NA | NA |
| 1824 | 6 | 1 | 912 | M | Dahomey | Brownsville | 1 | N | 260 | 10 | 22 | 0.932 | NA | NA | NA | 0 | 74 | 0.0000000 |
| 1825 | 6 | 1 | 913 | F | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1826 | 6 | 1 | 913 | M | Dahomey | Dahomey | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1827 | 6 | 1 | 914 | F | Israel | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1828 | 6 | 1 | 914 | M | Dahomey | Israel | 1 | L | 251 | 10 | 13 | 0.872 | NA | NA | NA | 0 | 35 | 0.0000000 |
| 1829 | 6 | 1 | 915 | F | Sweden | Dahomey | 1 | L | 226 | 9 | 12 | 1.096 | 30 | 37 | 67 | NA | NA | NA |
| 1830 | 6 | 1 | 915 | M | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1831 | 6 | 1 | 916 | F | Barcelona | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1832 | 6 | 1 | 916 | M | Israel | Barcelona | 1 | L | 270 | 11 | 8 | 0.865 | NA | NA | NA | 0 | 101 | 0.0000000 |
| 1833 | 6 | 1 | 917 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1834 | 6 | 1 | 917 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1835 | 6 | 1 | 918 | F | Dahomey | Israel | 1 | L | 259 | 10 | 21 | 0.959 | 0 | 0 | 0 | NA | NA | NA |
| 1836 | 6 | 1 | 918 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1837 | 6 | 1 | 919 | F | Israel | Israel | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1838 | 6 | 1 | 919 | M | Israel | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1839 | 6 | 1 | 920 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1840 | 6 | 1 | 920 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1843 | 6 | 1 | 922 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1844 | 6 | 1 | 922 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1845 | 6 | 1 | 923 | F | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1846 | 6 | 1 | 923 | M | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1847 | 6 | 1 | 924 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1848 | 6 | 1 | 924 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1849 | 6 | 1 | 925 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1850 | 6 | 1 | 925 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1851 | 6 | 1 | 926 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1852 | 6 | 1 | 926 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1853 | 6 | 1 | 927 | F | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1854 | 6 | 1 | 927 | M | Barcelona | Brownsville | 1 | L | 269 | 11 | 7 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1855 | 6 | 1 | 928 | F | Dahomey | Barcelona | 1 | L | 240 | 10 | 2 | 1.100 | 30 | 28 | 58 | NA | NA | NA |
| 1856 | 6 | 1 | 928 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1857 | 6 | 1 | 929 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1858 | 6 | 1 | 929 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1859 | 6 | 1 | 930 | F | Sweden | Barcelona | 1 | N | 252 | 10 | 14 | NA | 22 | 17 | 39 | NA | NA | NA |
| 1860 | 6 | 1 | 930 | M | Barcelona | Sweden | 1 | N | 241 | 10 | 3 | NA | NA | NA | NA | 0 | 107 | 0.0000000 |
| 1861 | 6 | 1 | 931 | F | Barcelona | Brownsville | 1 | L | 246 | 10 | 8 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1862 | 6 | 1 | 931 | M | Brownsville | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1863 | 6 | 1 | 932 | F | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1864 | 6 | 1 | 932 | M | Brownsville | Brownsville | 1 | L | 230 | 9 | 16 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1865 | 6 | 1 | 933 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1866 | 6 | 1 | 933 | M | Brownsville | Dahomey | 1 | L | 247 | 10 | 9 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1867 | 6 | 1 | 934 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1868 | 6 | 1 | 934 | M | Brownsville | Israel | 1 | L | 261 | 10 | 23 | 0.892 | NA | NA | NA | 0 | 56 | 0.0000000 |
| 1869 | 6 | 1 | 935 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1870 | 6 | 1 | 935 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1871 | 6 | 1 | 936 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1872 | 6 | 1 | 936 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1873 | 6 | 1 | 937 | F | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1874 | 6 | 1 | 937 | M | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1875 | 6 | 1 | 938 | F | Dahomey | Dahomey | 1 | N | 256 | 10 | 18 | 0.976 | 0 | 0 | 0 | NA | NA | NA |
| 1876 | 6 | 1 | 938 | M | Dahomey | Dahomey | 1 | N | 247 | 10 | 9 | NA | NA | NA | NA | 0 | 28 | 0.0000000 |
| 1877 | 6 | 1 | 939 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1878 | 6 | 1 | 939 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1879 | 6 | 1 | 940 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1880 | 6 | 1 | 940 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1881 | 6 | 1 | 941 | F | Barcelona | Israel | 1 | L | 247 | 10 | 9 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1882 | 6 | 1 | 941 | M | Israel | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1883 | 6 | 1 | 942 | F | Brownsville | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1884 | 6 | 1 | 942 | M | Israel | Brownsville | 1 | P | 257 | 10 | 19 | 0.918 | NA | NA | NA | 0 | 105 | 0.0000000 |
| 1885 | 6 | 1 | 943 | F | Dahomey | Israel | 1 | L | 254 | 10 | 16 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1886 | 6 | 1 | 943 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1887 | 6 | 1 | 944 | F | Israel | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1888 | 6 | 1 | 944 | M | Israel | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1889 | 6 | 1 | 945 | F | Sweden | Israel | 1 | N | 247 | 10 | 9 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1890 | 6 | 1 | 945 | M | Israel | Sweden | 1 | N | 239 | 9 | 1 | NA | NA | NA | NA | 0 | 65 | 0.0000000 |
| 1891 | 6 | 1 | 946 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1892 | 6 | 1 | 946 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1893 | 6 | 1 | 947 | F | Brownsville | Sweden | 1 | L | 239 | 9 | 1 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1894 | 6 | 1 | 947 | M | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1895 | 6 | 1 | 948 | F | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1896 | 6 | 1 | 948 | M | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1897 | 6 | 1 | 949 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1898 | 6 | 1 | 949 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1899 | 6 | 1 | 950 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1900 | 6 | 1 | 950 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1901 | 6 | 1 | 951 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1902 | 6 | 1 | 951 | M | Barcelona | Barcelona | 1 | P | 273 | 11 | 11 | 0.865 | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1903 | 6 | 1 | 952 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1904 | 6 | 1 | 952 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1905 | 6 | 1 | 953 | F | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1906 | 6 | 1 | 953 | M | Barcelona | Dahomey | 1 | L | 254 | 10 | 16 | 0.929 | NA | NA | NA | 0 | 35 | 0.0000000 |
| 1907 | 6 | 1 | 954 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1908 | 6 | 1 | 954 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1909 | 6 | 1 | 955 | F | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1910 | 6 | 1 | 955 | M | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1911 | 6 | 1 | 956 | F | Barcelona | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1912 | 6 | 1 | 956 | M | Brownsville | Barcelona | 1 | P | 247 | 10 | 9 | NA | NA | NA | NA | 0 | 48 | 0.0000000 |
| 1913 | 6 | 1 | 957 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1914 | 6 | 1 | 957 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1915 | 6 | 1 | 958 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1916 | 6 | 1 | 958 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1917 | 6 | 1 | 959 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1918 | 6 | 1 | 959 | M | Brownsville | Israel | 1 | L | 244 | 10 | 6 | 0.706 | NA | NA | NA | 0 | 118 | 0.0000000 |
| 1919 | 6 | 1 | 960 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1920 | 6 | 1 | 960 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1921 | 6 | 1 | 961 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1922 | 6 | 1 | 961 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1923 | 6 | 1 | 962 | F | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1924 | 6 | 1 | 962 | M | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1925 | 6 | 1 | 963 | F | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1926 | 6 | 1 | 963 | M | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1927 | 6 | 1 | 964 | F | Israel | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1928 | 6 | 1 | 964 | M | Dahomey | Israel | 1 | L | 249 | 10 | 11 | 1.078 | NA | NA | NA | 84 | 22 | 0.7924528 |
| 1929 | 6 | 1 | 965 | F | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1930 | 6 | 1 | 965 | M | Dahomey | Sweden | 1 | L | 243 | 10 | 5 | 1.008 | NA | NA | NA | 49 | 6 | 0.8909091 |
| 1931 | 6 | 1 | 966 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1932 | 6 | 1 | 966 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1933 | 6 | 1 | 967 | F | Brownsville | Israel | 1 | P | NA | NA | NA | 1.094 | 0 | 0 | 0 | NA | NA | NA |
| 1934 | 6 | 1 | 967 | M | Israel | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1935 | 6 | 1 | 968 | F | Dahomey | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1936 | 6 | 1 | 968 | M | Israel | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1937 | 6 | 1 | 969 | F | Israel | Israel | 1 | N | 270 | 11 | 8 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1938 | 6 | 1 | 969 | M | Israel | Israel | 1 | N | 268 | 11 | 6 | 0.844 | NA | NA | NA | 73 | 36 | 0.6697248 |
| 1939 | 6 | 1 | 970 | F | Sweden | Israel | 1 | N | 253 | 10 | 15 | 1.068 | 28 | 18 | 46 | NA | NA | NA |
| 1940 | 6 | 1 | 970 | M | Israel | Sweden | 1 | N | 271 | 11 | 9 | 0.900 | NA | NA | NA | 39 | 16 | 0.7090909 |
| 1941 | 6 | 1 | 971 | F | Barcelona | Sweden | 1 | P | 245 | 10 | 7 | 1.040 | 21 | 25 | 46 | NA | NA | NA |
| 1942 | 6 | 1 | 971 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1943 | 6 | 1 | 972 | F | Brownsville | Sweden | 1 | L | 241 | 10 | 3 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1944 | 6 | 1 | 972 | M | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1945 | 6 | 1 | 973 | F | Dahomey | Sweden | 1 | P | 251 | 10 | 13 | NA | 1 | 1 | 2 | NA | NA | NA |
| 1946 | 6 | 1 | 973 | M | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1951 | 6 | 1 | 976 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1952 | 6 | 1 | 976 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1953 | 6 | 1 | 977 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1954 | 6 | 1 | 977 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1955 | 6 | 1 | 978 | F | Dahomey | Barcelona | 1 | P | 257 | 10 | 19 | 0.985 | 22 | 32 | 54 | NA | NA | NA |
| 1956 | 6 | 1 | 978 | M | Barcelona | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1957 | 6 | 1 | 979 | F | Israel | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1958 | 6 | 1 | 979 | M | Barcelona | Israel | 1 | P | 277 | 11 | 15 | NA | NA | NA | NA | 0 | 66 | 0.0000000 |
| 1959 | 6 | 1 | 980 | F | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1960 | 6 | 1 | 980 | M | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1961 | 6 | 1 | 981 | F | Barcelona | Brownsville | 1 | N | 255 | 10 | 17 | 0.989 | 8 | 8 | 16 | NA | NA | NA |
| 1962 | 6 | 1 | 981 | M | Brownsville | Barcelona | 1 | N | 287 | 12 | 1 | 0.919 | NA | NA | NA | 0 | 66 | 0.0000000 |
| 1963 | 6 | 1 | 982 | F | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1964 | 6 | 1 | 982 | M | Brownsville | Brownsville | 1 | L | 247 | 10 | 9 | 0.999 | NA | NA | NA | 0 | 90 | 0.0000000 |
| 1965 | 6 | 1 | 983 | F | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1966 | 6 | 1 | 983 | M | Brownsville | Dahomey | 1 | L | NA | NA | NA | 0.910 | NA | NA | NA | 0 | 14 | 0.0000000 |
| 1967 | 6 | 1 | 984 | F | Israel | Brownsville | 0 | P | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1968 | 6 | 1 | 984 | M | Brownsville | Israel | 0 | P | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1969 | 6 | 1 | 985 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1970 | 6 | 1 | 985 | M | Brownsville | Sweden | 1 | P | 240 | 10 | 2 | 0.999 | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1971 | 6 | 1 | 986 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1972 | 6 | 1 | 986 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1973 | 6 | 1 | 987 | F | Brownsville | Dahomey | 1 | P | 242 | 10 | 4 | 1.024 | 29 | 30 | 59 | NA | NA | NA |
| 1974 | 6 | 1 | 987 | M | Dahomey | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1975 | 6 | 1 | 988 | F | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1976 | 6 | 1 | 988 | M | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1977 | 6 | 1 | 989 | F | Israel | Dahomey | 1 | L | 242 | 10 | 4 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1978 | 6 | 1 | 989 | M | Dahomey | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1979 | 6 | 1 | 990 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1980 | 6 | 1 | 990 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1981 | 6 | 1 | 991 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1982 | 6 | 1 | 991 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1983 | 6 | 1 | 992 | F | Brownsville | Israel | 1 | P | 245 | 10 | 7 | 0.996 | 23 | 18 | 41 | NA | NA | NA |
| 1984 | 6 | 1 | 992 | M | Israel | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1985 | 6 | 1 | 993 | F | Dahomey | Israel | 1 | L | 250 | 10 | 12 | NA | 0 | 0 | 0 | NA | NA | NA |
| 1986 | 6 | 1 | 993 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1987 | 6 | 1 | 994 | F | Israel | Israel | 1 | L | 272 | 11 | 10 | 0.994 | 2 | 4 | 6 | NA | NA | NA |
| 1988 | 6 | 1 | 994 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1989 | 6 | 1 | 995 | F | Sweden | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1990 | 6 | 1 | 995 | M | Israel | Sweden | 1 | L | 243 | 10 | 5 | 1.012 | NA | NA | NA | 0 | 4 | 0.0000000 |
| 1991 | 6 | 1 | 996 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1992 | 6 | 1 | 996 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1993 | 6 | 1 | 997 | F | Brownsville | Sweden | 1 | N | 242 | 10 | 4 | 1.033 | 26 | 28 | 54 | NA | NA | NA |
| 1994 | 6 | 1 | 997 | M | Sweden | Brownsville | 1 | N | 257 | 10 | 19 | 0.906 | NA | NA | NA | 48 | 60 | 0.4444444 |
| 1995 | 6 | 1 | 998 | F | Dahomey | Sweden | 1 | L | 275 | 11 | 13 | 0.908 | 0 | 0 | 0 | NA | NA | NA |
| 1996 | 6 | 1 | 998 | M | Sweden | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 1997 | 6 | 1 | 999 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 1998 | 6 | 1 | 999 | M | Sweden | Israel | 1 | L | 248 | 10 | 10 | 0.987 | NA | NA | NA | 124 | 23 | 0.8435374 |
| 1999 | 6 | 1 | 1000 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2000 | 6 | 1 | 1000 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2001 | 6 | 1 | 1001 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2002 | 6 | 1 | 1001 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2003 | 6 | 1 | 1002 | F | Brownsville | Barcelona | 1 | N | 269 | 11 | 7 | 1.042 | 23 | 15 | 38 | NA | NA | NA |
| 2004 | 6 | 1 | 1002 | M | Barcelona | Brownsville | 1 | N | 271 | 11 | 9 | 0.963 | NA | NA | NA | 97 | 24 | 0.8016529 |
| 2005 | 6 | 1 | 1003 | F | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2006 | 6 | 1 | 1003 | M | Barcelona | Dahomey | 1 | P | 244 | 10 | 6 | 1.059 | NA | NA | NA | 58 | 9 | 0.8656716 |
| 2007 | 6 | 1 | 1004 | F | Israel | Barcelona | 1 | P | 250 | 10 | 12 | NA | 27 | 21 | 48 | NA | NA | NA |
| 2008 | 6 | 1 | 1004 | M | Barcelona | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2009 | 6 | 1 | 1005 | F | Sweden | Barcelona | 1 | P | 248 | 10 | 10 | 1.149 | 23 | 20 | 43 | NA | NA | NA |
| 2010 | 6 | 1 | 1005 | M | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2011 | 6 | 1 | 1006 | F | Barcelona | Brownsville | 1 | N | 274 | 11 | 12 | NA | 0 | 0 | 0 | NA | NA | NA |
| 2012 | 6 | 1 | 1006 | M | Brownsville | Barcelona | 1 | N | 242 | 10 | 4 | 1.030 | NA | NA | NA | 0 | 32 | 0.0000000 |
| 2013 | 6 | 1 | 1007 | F | Brownsville | Brownsville | 1 | N | 254 | 10 | 16 | NA | 0 | 0 | 0 | NA | NA | NA |
| 2014 | 6 | 1 | 1007 | M | Brownsville | Brownsville | 1 | N | 243 | 10 | 5 | 0.947 | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2015 | 6 | 1 | 1008 | F | Dahomey | Brownsville | 1 | L | 253 | 10 | 15 | 1.157 | 48 | 26 | 74 | NA | NA | NA |
| 2016 | 6 | 1 | 1008 | M | Brownsville | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2017 | 6 | 1 | 1009 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2018 | 6 | 1 | 1009 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2019 | 6 | 1 | 1010 | F | Sweden | Brownsville | 1 | N | 266 | 11 | 4 | 0.998 | 1 | 2 | 3 | NA | NA | NA |
| 2020 | 6 | 1 | 1010 | M | Brownsville | Sweden | 1 | N | 288 | 12 | 2 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2021 | 6 | 1 | 1011 | F | Barcelona | Dahomey | 1 | N | 247 | 10 | 9 | 1.092 | 16 | 26 | 42 | NA | NA | NA |
| 2022 | 6 | 1 | 1011 | M | Dahomey | Barcelona | 1 | N | 250 | 10 | 12 | 1.060 | NA | NA | NA | 45 | 3 | 0.9375000 |
| 2023 | 6 | 1 | 1012 | F | Brownsville | Dahomey | 1 | N | 272 | 11 | 10 | 1.005 | 14 | 21 | 35 | NA | NA | NA |
| 2024 | 6 | 1 | 1012 | M | Dahomey | Brownsville | 1 | N | 284 | 11 | 22 | 1.021 | NA | NA | NA | 4 | 0 | 1.0000000 |
| 2025 | 6 | 1 | 1013 | F | Dahomey | Dahomey | 1 | P | 245 | 10 | 7 | 1.074 | 38 | 32 | 70 | NA | NA | NA |
| 2026 | 6 | 1 | 1013 | M | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2027 | 6 | 1 | 1014 | F | Israel | Dahomey | 1 | N | 274 | 11 | 12 | 0.967 | 0 | 0 | 0 | NA | NA | NA |
| 2028 | 6 | 1 | 1014 | M | Dahomey | Israel | 1 | N | 241 | 10 | 3 | 1.042 | NA | NA | NA | 0 | 54 | 0.0000000 |
| 2029 | 6 | 1 | 1015 | F | Sweden | Dahomey | 1 | L | 240 | 10 | 2 | NA | 33 | 31 | 64 | NA | NA | NA |
| 2030 | 6 | 1 | 1015 | M | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2031 | 6 | 1 | 1016 | F | Barcelona | Israel | 1 | P | 248 | 10 | 10 | 1.106 | 22 | 30 | 52 | NA | NA | NA |
| 2032 | 6 | 1 | 1016 | M | Israel | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2033 | 6 | 1 | 1017 | F | Brownsville | Israel | 1 | N | 245 | 10 | 7 | 1.063 | 7 | 9 | 16 | NA | NA | NA |
| 2034 | 6 | 1 | 1017 | M | Israel | Brownsville | 1 | N | 272 | 11 | 10 | 0.876 | NA | NA | NA | 0 | 96 | 0.0000000 |
| 2035 | 6 | 1 | 1018 | F | Dahomey | Israel | 1 | N | 252 | 10 | 14 | 0.985 | 18 | 21 | 39 | NA | NA | NA |
| 2036 | 6 | 1 | 1018 | M | Israel | Dahomey | 1 | N | 263 | 10 | 1 | 0.904 | NA | NA | NA | 0 | 58 | 0.0000000 |
| 2037 | 6 | 1 | 1019 | F | Israel | Israel | 1 | L | 231 | 9 | 17 | 1.053 | 28 | 25 | 53 | NA | NA | NA |
| 2038 | 6 | 1 | 1019 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2039 | 6 | 1 | 1020 | F | Sweden | Israel | 1 | N | 238 | 9 | 0 | 1.205 | 0 | 0 | 0 | NA | NA | NA |
| 2040 | 6 | 1 | 1020 | M | Israel | Sweden | 1 | N | 247 | 10 | 9 | NA | NA | NA | NA | NA | NA | NA |
| 2041 | 6 | 1 | 1021 | F | Barcelona | Sweden | 1 | L | 273 | 11 | 11 | 1.106 | 31 | 38 | 69 | NA | NA | NA |
| 2042 | 6 | 1 | 1021 | M | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2043 | 6 | 1 | 1022 | F | Brownsville | Sweden | 1 | L | 275 | 11 | 13 | NA | 0 | 0 | 0 | NA | NA | NA |
| 2044 | 6 | 1 | 1022 | M | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2045 | 6 | 1 | 1023 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2046 | 6 | 1 | 1023 | M | Sweden | Dahomey | 1 | L | 252 | 10 | 14 | NA | NA | NA | NA | 0 | 19 | 0.0000000 |
| 2049 | 6 | 1 | 1025 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2050 | 6 | 1 | 1025 | M | Sweden | Sweden | 1 | L | 268 | 11 | 6 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2051 | 6 | 1 | 1026 | F | Barcelona | Barcelona | 1 | N | 257 | 10 | 19 | 1.090 | 21 | 26 | 47 | NA | NA | NA |
| 2052 | 6 | 1 | 1026 | M | Barcelona | Barcelona | 1 | N | 255 | 10 | 17 | 0.995 | NA | NA | NA | 90 | 0 | 1.0000000 |
| 2053 | 6 | 1 | 1027 | F | Brownsville | Barcelona | 1 | N | 270 | 11 | 8 | NA | 0 | 0 | 0 | NA | NA | NA |
| 2054 | 6 | 1 | 1027 | M | Barcelona | Brownsville | 1 | N | 255 | 10 | 17 | 0.995 | NA | NA | NA | 0 | 16 | 0.0000000 |
| 2055 | 6 | 1 | 1028 | F | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2056 | 6 | 1 | 1028 | M | Barcelona | Dahomey | 1 | L | 255 | 10 | 17 | 0.973 | NA | NA | NA | 70 | 68 | 0.5072464 |
| 2057 | 6 | 1 | 1029 | F | Israel | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2058 | 6 | 1 | 1029 | M | Barcelona | Israel | 1 | L | 275 | 11 | 13 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2059 | 6 | 1 | 1030 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2060 | 6 | 1 | 1030 | M | Barcelona | Sweden | 1 | L | 268 | 11 | 6 | 0.965 | NA | NA | NA | 81 | 33 | 0.7105263 |
| 2063 | 6 | 1 | 1032 | F | Brownsville | Brownsville | 1 | L | 245 | 10 | 7 | 1.165 | 39 | 34 | 73 | NA | NA | NA |
| 2064 | 6 | 1 | 1032 | M | Brownsville | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2065 | 6 | 1 | 1033 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2066 | 6 | 1 | 1033 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2067 | 6 | 1 | 1034 | F | Israel | Brownsville | 1 | N | 250 | 10 | 12 | 1.070 | 24 | 25 | 49 | NA | NA | NA |
| 2068 | 6 | 1 | 1034 | M | Brownsville | Israel | 1 | N | 254 | 10 | 16 | NA | NA | NA | NA | 0 | 99 | 0.0000000 |
| 2069 | 6 | 1 | 1035 | F | Sweden | Brownsville | 1 | N | 258 | 10 | 20 | 0.994 | 0 | 0 | 0 | NA | NA | NA |
| 2070 | 6 | 1 | 1035 | M | Brownsville | Sweden | 1 | N | 274 | 11 | 12 | 0.902 | NA | NA | NA | 0 | 43 | 0.0000000 |
| 2071 | 6 | 1 | 1036 | F | Barcelona | Dahomey | 1 | N | 241 | 10 | 3 | 1.103 | 22 | 23 | 45 | NA | NA | NA |
| 2072 | 6 | 1 | 1036 | M | Dahomey | Barcelona | 1 | N | 254 | 10 | 16 | 0.981 | NA | NA | NA | 14 | 29 | 0.3255814 |
| 2073 | 6 | 1 | 1037 | F | Brownsville | Dahomey | 1 | N | 230 | 9 | 16 | 0.916 | 20 | 20 | 40 | NA | NA | NA |
| 2074 | 6 | 1 | 1037 | M | Dahomey | Brownsville | 1 | N | 242 | 10 | 4 | 0.995 | NA | NA | NA | 0 | 17 | 0.0000000 |
| 2075 | 6 | 1 | 1038 | F | Dahomey | Dahomey | 1 | L | 252 | 10 | 14 | 1.102 | 27 | 28 | 55 | NA | NA | NA |
| 2076 | 6 | 1 | 1038 | M | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2077 | 6 | 1 | 1039 | F | Israel | Dahomey | 1 | N | 259 | 10 | 21 | 1.076 | 19 | 18 | 37 | NA | NA | NA |
| 2078 | 6 | 1 | 1039 | M | Dahomey | Israel | 1 | N | 275 | 11 | 13 | 0.944 | NA | NA | NA | 121 | 0 | 1.0000000 |
| 2079 | 6 | 1 | 1040 | F | Sweden | Dahomey | 1 | L | 269 | 11 | 7 | 1.003 | 24 | 23 | 47 | NA | NA | NA |
| 2080 | 6 | 1 | 1040 | M | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2081 | 6 | 1 | 1041 | F | Barcelona | Israel | 1 | L | 245 | 10 | 7 | 1.212 | 0 | 0 | 0 | NA | NA | NA |
| 2082 | 6 | 1 | 1041 | M | Israel | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2083 | 6 | 1 | 1042 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2084 | 6 | 1 | 1042 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2087 | 6 | 1 | 1044 | F | Israel | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2088 | 6 | 1 | 1044 | M | Israel | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2089 | 6 | 1 | 1045 | F | Sweden | Israel | 1 | L | 276 | 11 | 14 | 0.940 | 6 | 13 | 19 | NA | NA | NA |
| 2090 | 6 | 1 | 1045 | M | Israel | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2091 | 6 | 1 | 1046 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2092 | 6 | 1 | 1046 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2093 | 6 | 1 | 1047 | F | Brownsville | Sweden | 1 | L | 254 | 10 | 16 | 0.897 | 8 | 14 | 22 | NA | NA | NA |
| 2094 | 6 | 1 | 1047 | M | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2095 | 6 | 1 | 1048 | F | Dahomey | Sweden | 1 | N | 252 | 10 | 14 | 1.011 | 17 | 27 | 44 | NA | NA | NA |
| 2096 | 6 | 1 | 1048 | M | Sweden | Dahomey | 1 | N | 262 | 10 | 0 | 0.970 | NA | NA | NA | 106 | 8 | 0.9298246 |
| 2097 | 6 | 1 | 1049 | F | Israel | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2098 | 6 | 1 | 1049 | M | Sweden | Israel | 1 | L | 286 | 12 | 0 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2099 | 6 | 1 | 1050 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2100 | 6 | 1 | 1050 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2101 | 6 | 1 | 1051 | F | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2102 | 6 | 1 | 1051 | M | Barcelona | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2103 | 6 | 1 | 1052 | F | Brownsville | Barcelona | 1 | N | 252 | 10 | 14 | 1.085 | 27 | 28 | 55 | NA | NA | NA |
| 2104 | 6 | 1 | 1052 | M | Barcelona | Brownsville | 1 | N | 277 | 11 | 15 | 0.917 | NA | NA | NA | 0 | 82 | 0.0000000 |
| 2105 | 6 | 1 | 1053 | F | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2106 | 6 | 1 | 1053 | M | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2107 | 6 | 1 | 1054 | F | Israel | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2108 | 6 | 1 | 1054 | M | Barcelona | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2109 | 6 | 1 | 1055 | F | Sweden | Barcelona | 1 | P | 259 | 10 | 21 | 0.936 | 10 | 9 | 19 | NA | NA | NA |
| 2110 | 6 | 1 | 1055 | M | Barcelona | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2111 | 6 | 1 | 1056 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2112 | 6 | 1 | 1056 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2113 | 6 | 1 | 1057 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2114 | 6 | 1 | 1057 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2115 | 6 | 1 | 1058 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2116 | 6 | 1 | 1058 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2117 | 6 | 1 | 1059 | F | Israel | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2118 | 6 | 1 | 1059 | M | Brownsville | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2119 | 6 | 1 | 1060 | F | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2120 | 6 | 1 | 1060 | M | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2121 | 6 | 1 | 1061 | F | Barcelona | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2122 | 6 | 1 | 1061 | M | Dahomey | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2123 | 6 | 1 | 1062 | F | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2124 | 6 | 1 | 1062 | M | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2125 | 6 | 1 | 1063 | F | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2126 | 6 | 1 | 1063 | M | Dahomey | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2127 | 6 | 1 | 1064 | F | Israel | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2128 | 6 | 1 | 1064 | M | Dahomey | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2129 | 6 | 1 | 1065 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2130 | 6 | 1 | 1065 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2131 | 6 | 1 | 1066 | F | Barcelona | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2132 | 6 | 1 | 1066 | M | Israel | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2133 | 6 | 1 | 1067 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2134 | 6 | 1 | 1067 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2135 | 6 | 1 | 1068 | F | Dahomey | Israel | 1 | N | 256 | 10 | 18 | 0.999 | 28 | 18 | 46 | NA | NA | NA |
| 2136 | 6 | 1 | 1068 | M | Israel | Dahomey | 1 | N | 275 | 11 | 13 | 0.827 | NA | NA | NA | 0 | 30 | 0.0000000 |
| 2137 | 6 | 1 | 1069 | F | Israel | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2138 | 6 | 1 | 1069 | M | Israel | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2139 | 6 | 1 | 1070 | F | Sweden | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2140 | 6 | 1 | 1070 | M | Israel | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2141 | 6 | 1 | 1071 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2142 | 6 | 1 | 1071 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2143 | 6 | 1 | 1072 | F | Brownsville | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2144 | 6 | 1 | 1072 | M | Sweden | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2145 | 6 | 1 | 1073 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2146 | 6 | 1 | 1073 | M | Sweden | Dahomey | 1 | P | 274 | 11 | 12 | NA | NA | NA | NA | 0 | 49 | 0.0000000 |
| 2147 | 6 | 1 | 1074 | F | Israel | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2148 | 6 | 1 | 1074 | M | Sweden | Israel | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2149 | 6 | 1 | 1075 | F | Sweden | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2150 | 6 | 1 | 1075 | M | Sweden | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2151 | 6 | 1 | 1076 | F | Barcelona | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2152 | 6 | 1 | 1076 | M | Barcelona | Barcelona | 1 | L | 244 | 10 | 6 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2153 | 6 | 1 | 1077 | F | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2154 | 6 | 1 | 1077 | M | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2155 | 6 | 1 | 1078 | F | Dahomey | Barcelona | 1 | N | 256 | 10 | 18 | 1.080 | 13 | 4 | 17 | NA | NA | NA |
| 2156 | 6 | 1 | 1078 | M | Barcelona | Dahomey | 1 | N | 245 | 10 | 7 | 1.017 | NA | NA | NA | 46 | 38 | 0.5476190 |
| 2157 | 6 | 1 | 1079 | F | Israel | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2158 | 6 | 1 | 1079 | M | Barcelona | Israel | 1 | L | 243 | 10 | 5 | 1.059 | NA | NA | NA | 50 | 2 | 0.9615385 |
| 2159 | 6 | 1 | 1080 | F | Sweden | Barcelona | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2160 | 6 | 1 | 1080 | M | Barcelona | Sweden | 1 | P | 261 | 10 | 23 | 0.952 | NA | NA | NA | 107 | 53 | 0.6687500 |
| 2161 | 6 | 1 | 1081 | F | Barcelona | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2162 | 6 | 1 | 1081 | M | Brownsville | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2163 | 6 | 1 | 1082 | F | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2164 | 6 | 1 | 1082 | M | Brownsville | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2165 | 6 | 1 | 1083 | F | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2166 | 6 | 1 | 1083 | M | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2167 | 6 | 1 | 1084 | F | Israel | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2168 | 6 | 1 | 1084 | M | Brownsville | Israel | 1 | P | 269 | 11 | 7 | NA | NA | NA | NA | 0 | 79 | 0.0000000 |
| 2169 | 6 | 1 | 1085 | F | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2170 | 6 | 1 | 1085 | M | Brownsville | Sweden | 1 | P | 260 | 10 | 22 | 0.993 | NA | NA | NA | 0 | 45 | 0.0000000 |
| 2171 | 6 | 1 | 1086 | F | Barcelona | Dahomey | 1 | L | 258 | 10 | 20 | 1.057 | 25 | 28 | 53 | NA | NA | NA |
| 2172 | 6 | 1 | 1086 | M | Dahomey | Barcelona | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2173 | 6 | 1 | 1087 | F | Brownsville | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2174 | 6 | 1 | 1087 | M | Dahomey | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2175 | 6 | 1 | 1088 | F | Dahomey | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2176 | 6 | 1 | 1088 | M | Dahomey | Dahomey | 1 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2177 | 6 | 1 | 1089 | F | Israel | Dahomey | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2178 | 6 | 1 | 1089 | M | Dahomey | Israel | 1 | L | 262 | 10 | 0 | 0.988 | NA | NA | NA | 0 | 48 | 0.0000000 |
| 2179 | 6 | 1 | 1090 | F | Sweden | Dahomey | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2180 | 6 | 1 | 1090 | M | Dahomey | Sweden | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2181 | 6 | 1 | 1091 | F | Barcelona | Israel | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2182 | 6 | 1 | 1091 | M | Israel | Barcelona | 1 | P | 257 | 10 | 19 | NA | NA | NA | NA | NA | NA | NA |
| 2183 | 6 | 1 | 1092 | F | Brownsville | Israel | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2184 | 6 | 1 | 1092 | M | Israel | Brownsville | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2185 | 6 | 1 | 1093 | F | Dahomey | Israel | 1 | P | 275 | 11 | 13 | NA | 13 | 18 | 31 | NA | NA | NA |
| 2186 | 6 | 1 | 1093 | M | Israel | Dahomey | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2187 | 6 | 1 | 1094 | F | Israel | Israel | 1 | P | 245 | 10 | 7 | 1.100 | 19 | 24 | 43 | NA | NA | NA |
| 2188 | 6 | 1 | 1094 | M | Israel | Israel | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2189 | 6 | 1 | 1095 | F | Sweden | Israel | 1 | L | 251 | 10 | 13 | 1.124 | 21 | 45 | 66 | NA | NA | NA |
| 2190 | 6 | 1 | 1095 | M | Israel | Sweden | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2191 | 6 | 1 | 1096 | F | Barcelona | Sweden | 0 | L | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2192 | 6 | 1 | 1096 | M | Sweden | Barcelona | 0 | L | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2193 | 6 | 1 | 1097 | F | Brownsville | Sweden | 1 | L | 275 | 11 | 13 | NA | 0 | 0 | 0 | NA | NA | NA |
| 2194 | 6 | 1 | 1097 | M | Sweden | Brownsville | 0 | N | NA | NA | NA | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2195 | 6 | 1 | 1098 | F | Dahomey | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2196 | 6 | 1 | 1098 | M | Sweden | Dahomey | 1 | L | 253 | 10 | 15 | 1.071 | NA | NA | NA | 58 | 81 | 0.4172662 |
| 2197 | 6 | 1 | 1099 | F | Israel | Sweden | 1 | N | NA | NA | NA | 1.114 | 9 | 14 | 23 | NA | NA | NA |
| 2198 | 6 | 1 | 1099 | M | Sweden | Israel | 1 | N | 278 | 11 | 16 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
| 2199 | 6 | 1 | 1100 | F | Sweden | Sweden | 0 | N | NA | NA | NA | NA | 0 | 0 | 0 | NA | NA | NA |
| 2200 | 6 | 1 | 1100 | M | Sweden | Sweden | 1 | P | 274 | 11 | 12 | NA | NA | NA | NA | 0 | 0 | 0.0000000 |
Columns represent:
Individual: the focal fly being tested.
Block: the distinct peirod of time that the particular individual was tested.
Duplicate: Was the fly from the first independent mitochondrial duplicate copy or the second?
Replicate: A set of all possible combinations of the 5 haplotypes. Each replicate contained 25 cells.
Sex: was the focal individual female or male?
Focal_haplotype: what mtDNA haplotype did the focal individual carry?
Social_haplotype: what mtDNA haplotype did the social competitor of the focal individual carry?
Survived: did the focal individual die as a larva (L), as a pupa (P) or survive to adutlhood (N)?
Social_survival: did the social competitor die as a larva (L), as a pupa (P) or survive to adutlhood (N)?
Dev_time: how many hours did it take for the focal individual to progress from an egg to an adult. NA values indicate where individuals did not survive or development time could not be measured.
Day: how many days did it take the focal individual to develop?
Hours: lights were turned on at 7am every morning. How many hours did it take for individuals to eclose after this time?
Wing_length: what was the length in mm of the focal individuals right wing?
Maternal_female_offspring: how many adult female offspring did a focal female produce in a two day period?
Maternal_male_offspring: how many adult male offspring did a focal female produce in a two day period?
Maternal_total_offspring: how many adult offspring did a focal female produce in a two day period?
Paternal_focal_offspring: how many red-eye phenotype offspring were there across the two vials in the male adult fitness assay?
Paternal_bw_offspring: how many brown-eye phenotype offspring were there across the two vials in the male adult fitness assay?
This section provides information on the operating system and R packages attached during the production of this document, to allow easier replication of the analysis.
sessionInfo() %>% pander
R version 3.6.1 (2019-07-05)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
locale: en_AU.UTF-8||en_AU.UTF-8||en_AU.UTF-8||C||en_AU.UTF-8||en_AU.UTF-8
attached base packages: stats, graphics, grDevices, utils, datasets, methods and base
other attached packages: groupdata2(v.1.1.2), forcats(v.0.4.0), stringr(v.1.4.0), pander(v.0.6.3), kableExtra(v.1.1.0), ggResidpanel(v.0.3.0), ggbeeswarm(v.0.6.0), ggpubr(v.0.2.2), magrittr(v.1.5), ggstance(v.0.3.2), ggExtra(v.0.8), ggridges(v.0.5.1), ggThemeAssist(v.0.1.5), ggplot2(v.3.2.1), MuMIn(v.1.43.6), dplyr(v.0.8.3), car(v.3.0-3), carData(v.3.0-2), brms(v.2.9.0), Rcpp(v.1.0.2), glmmTMB(v.0.2.3), lmerTest(v.3.1-0), lme4(v.1.1-21) and Matrix(v.1.2-17)
loaded via a namespace (and not attached): minqa(v.1.2.4), colorspace(v.1.4-1), ggsignif(v.0.6.0), rio(v.0.5.16), rsconnect(v.0.8.15), markdown(v.1.1), base64enc(v.0.1-3), rstudioapi(v.0.10), rstan(v.2.19.2), DT(v.0.8), xml2(v.1.2.2), bridgesampling(v.0.7-2), splines(v.3.6.1), robustbase(v.0.93-5), knitr(v.1.24), shinythemes(v.1.1.2), zeallot(v.0.1.0), bayesplot(v.1.7.0), jsonlite(v.1.6), nloptr(v.1.2.1), shiny(v.1.3.2), readr(v.1.3.1), httr(v.1.4.1), compiler(v.3.6.1), backports(v.1.1.4), assertthat(v.0.2.1), lazyeval(v.0.2.2), cli(v.1.1.0), later(v.0.8.0), formatR(v.1.7), htmltools(v.0.3.6), prettyunits(v.1.0.2), tools(v.3.6.1), igraph(v.1.2.4.1), coda(v.0.19-3), gtable(v.0.3.0), glue(v.1.3.1), reshape2(v.1.4.3), cellranger(v.1.1.0), vctrs(v.0.2.0), nlme(v.3.1-140), crosstalk(v.1.0.0), xfun(v.0.8), ps(v.1.3.0), rvest(v.0.3.4), openxlsx(v.4.1.0.1), mime(v.0.7), miniUI(v.0.1.1.1), gtools(v.3.8.1), DEoptimR(v.1.0-8), MASS(v.7.3-51.4), zoo(v.1.8-6), scales(v.1.0.0), colourpicker(v.1.0), hms(v.0.5.0), promises(v.1.0.1), Brobdingnag(v.1.2-6), parallel(v.3.6.1), inline(v.0.3.15), qqplotr(v.0.0.3), shinystan(v.2.5.0), TMB(v.1.7.15), yaml(v.2.2.0), curl(v.4.0), gridExtra(v.2.3), loo(v.2.1.0), StanHeaders(v.2.18.1-10), stringi(v.1.4.3), highr(v.0.8), dygraphs(v.1.1.1.6), boot(v.1.3-22), pkgbuild(v.1.0.4), zip(v.2.0.3), rlang(v.0.4.0), pkgconfig(v.2.0.2), matrixStats(v.0.54.0), evaluate(v.0.14), lattice(v.0.20-38), purrr(v.0.3.2), labeling(v.0.3), rstantools(v.1.5.1), htmlwidgets(v.1.3), cowplot(v.1.0.0), processx(v.3.4.1), tidyselect(v.0.2.5), plyr(v.1.8.4), R6(v.2.4.0), pillar(v.1.4.2), haven(v.2.1.1), foreign(v.0.8-71), withr(v.2.1.2), xts(v.0.11-2), abind(v.1.4-5), tibble(v.2.1.3), crayon(v.1.3.4), plotly(v.4.9.0), rmarkdown(v.1.14), grid(v.3.6.1), readxl(v.1.3.1), data.table(v.1.12.2), callr(v.3.3.1), threejs(v.0.3.1), webshot(v.0.5.1), digest(v.0.6.20), xtable(v.1.8-4), tidyr(v.0.8.3), httpuv(v.1.5.1), numDeriv(v.2016.8-1.1), stats4(v.3.6.1), munsell(v.0.5.0), viridisLite(v.0.3.0), beeswarm(v.0.2.3), vipor(v.0.4.5) and shinyjs(v.1.0)
Brooks, Mollie E, Kasper Kristensen, Koen J van Benthem, Arni Magnusson, Casper W Berg, Anders Nielsen, Hans J Skaug, Martin Maechler, and Benjamin M Bolker. 2017. “Modeling Zero-Inflated Count Data with glmmTMB.” Journal Article. BioRxiv, 132753.
Symonds, Matthew R. E., and Adnan Moussalli. 2011. “A Brief Guide to Model Selection, Multimodel Inference and Model Averaging in Behavioural Ecology Using Akaike’s Information Criterion.” Journal Article. Behavioral Ecology and Sociobiology 65 (1): 13–21. https://doi.org/10.1007/s00265-010-1037-6.